Overview

Dataset statistics

 No AttritionAttrition
Number of variables3535
Number of observations1233237
Missing cells00
Missing cells (%)0.0%0.0%
Duplicate rows00
Duplicate rows (%)0.0%0.0%
Total size in memory346.8 KiB66.7 KiB
Average record size in memory288.0 B288.0 B

Variable types

 No AttritionAttrition
Numeric1515
Boolean33
Categorical1717

Alerts

No AttritionAttrition
Attrition has constant value "" Attrition has constant value "" Constant
EmployeeCount has constant value "" EmployeeCount has constant value "" Constant
Over18 has constant value "" Over18 has constant value "" Constant
StandardHours has constant value "" StandardHours has constant value "" Constant
Age is highly overall correlated with TotalWorkingYearsAge is highly overall correlated with MonthlyIncome and 1 other fieldsHigh Correlation
MonthlyIncome is highly overall correlated with TotalWorkingYears and 1 other fieldsMonthlyIncome is highly overall correlated with Age and 3 other fieldsHigh Correlation
PercentSalaryHike is highly overall correlated with PerformanceRatingPercentSalaryHike is highly overall correlated with PerformanceRatingHigh Correlation
TotalWorkingYears is highly overall correlated with Age and 3 other fieldsTotalWorkingYears is highly overall correlated with Age and 5 other fieldsHigh Correlation
YearsAtCompany is highly overall correlated with TotalWorkingYears and 2 other fieldsYearsAtCompany is highly overall correlated with MonthlyIncome and 5 other fieldsHigh Correlation
YearsInCurrentRole is highly overall correlated with YearsAtCompany and 1 other fieldsYearsInCurrentRole is highly overall correlated with TotalWorkingYears and 3 other fieldsHigh Correlation
YearsWithCurrManager is highly overall correlated with YearsAtCompany and 1 other fieldsYearsWithCurrManager is highly overall correlated with TotalWorkingYears and 3 other fieldsHigh Correlation
Department is highly overall correlated with EducationField and 1 other fieldsDepartment is highly overall correlated with EducationField and 1 other fieldsHigh Correlation
EducationField is highly overall correlated with DepartmentEducationField is highly overall correlated with DepartmentHigh Correlation
JobLevel is highly overall correlated with MonthlyIncome and 2 other fieldsJobLevel is highly overall correlated with MonthlyIncome and 3 other fieldsHigh Correlation
JobRole is highly overall correlated with Department and 1 other fieldsJobRole is highly overall correlated with Department and 1 other fieldsHigh Correlation
MaritalStatus is highly overall correlated with StockOptionLevelMaritalStatus is highly overall correlated with StockOptionLevelHigh Correlation
PerformanceRating is highly overall correlated with PercentSalaryHikePerformanceRating is highly overall correlated with PercentSalaryHikeHigh Correlation
StockOptionLevel is highly overall correlated with MaritalStatusStockOptionLevel is highly overall correlated with MaritalStatusHigh Correlation
EmployeeNumber has unique values EmployeeNumber has unique values Unique
NumCompaniesWorked has 174 (14.1%) zeros NumCompaniesWorked has 23 (9.7%) zeros Zeros
TrainingTimesLastYear has 39 (3.2%) zeros TrainingTimesLastYear has 15 (6.3%) zeros Zeros
YearsAtCompany has 28 (2.3%) zeros YearsAtCompany has 16 (6.8%) zeros Zeros
YearsInCurrentRole has 171 (13.9%) zeros YearsInCurrentRole has 73 (30.8%) zeros Zeros
YearsSinceLastPromotion has 471 (38.2%) zeros YearsSinceLastPromotion has 110 (46.4%) zeros Zeros
YearsWithCurrManager has 178 (14.4%) zeros YearsWithCurrManager has 85 (35.9%) zeros Zeros
Alert not present in YearsSinceLastPromotion is highly overall correlated with YearsAtCompany and 2 other fieldsHigh Correlation
Alert not present in TotalWorkingYears has 5 (2.1%) zeros Zeros

Reproduction

 No AttritionAttrition
Analysis started2023-05-20 13:43:03.0724902023-05-20 13:43:31.252602
Analysis finished2023-05-20 13:43:31.2506552023-05-20 13:43:57.227301
Duration28.18 seconds25.97 seconds
Software versionydata-profiling vv4.1.2ydata-profiling vv4.1.2
Download configurationconfig.jsonconfig.json

Variables

Age
Real number (ℝ)

 No AttritionAttrition
Distinct4339
Distinct (%)3.5%16.5%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean37.56123333.607595
 No AttritionAttrition
Minimum1818
Maximum6058
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
2023-05-20T15:43:57.415148image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

 No AttritionAttrition
Minimum1818
5-th percentile2520
Q13128
median3632
Q34339
95-th percentile5453
Maximum6058
Range4240
Interquartile range (IQR)1211

Descriptive statistics

 No AttritionAttrition
Standard deviation8.888369.6893499
Coefficient of variation (CV)0.236636540.28830834
Kurtosis-0.41183492-0.057043693
Mean37.56123333.607595
Median Absolute Deviation (MAD)66
Skewness0.408121690.71573239
Sum463137965
Variance79.00294493.883501
MonotonicityNot monotonicNot monotonic
2023-05-20T15:43:57.582343image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
34 68
 
5.5%
35 68
 
5.5%
36 63
 
5.1%
38 56
 
4.5%
40 52
 
4.2%
31 51
 
4.1%
30 51
 
4.1%
29 50
 
4.1%
32 50
 
4.1%
33 46
 
3.7%
Other values (33) 678
55.0%
ValueCountFrequency (%)
31 18
 
7.6%
29 18
 
7.6%
28 14
 
5.9%
33 12
 
5.1%
26 12
 
5.1%
32 11
 
4.6%
35 10
 
4.2%
34 9
 
3.8%
30 9
 
3.8%
24 7
 
3.0%
Other values (29) 117
49.4%
ValueCountFrequency (%)
18 4
 
0.3%
19 3
 
0.2%
20 5
 
0.4%
21 7
 
0.6%
22 11
 
0.9%
23 10
 
0.8%
24 19
1.5%
25 20
1.6%
26 27
2.2%
27 45
3.6%
ValueCountFrequency (%)
18 4
 
1.7%
19 6
2.5%
20 6
2.5%
21 6
2.5%
22 5
2.1%
23 4
 
1.7%
24 7
3.0%
25 6
2.5%
26 12
5.1%
27 3
 
1.3%
ValueCountFrequency (%)
18 4
 
0.3%
19 6
0.5%
20 6
0.5%
21 6
0.5%
22 5
0.4%
23 4
 
0.3%
24 7
0.6%
25 6
0.5%
26 12
1.0%
27 3
 
0.2%
ValueCountFrequency (%)
18 4
 
1.7%
19 3
 
1.3%
20 5
 
2.1%
21 7
 
3.0%
22 11
 
4.6%
23 10
 
4.2%
24 19
8.0%
25 20
8.4%
26 27
11.4%
27 45
19.0%

Attrition
Boolean

 No AttritionAttrition
Distinct11
Distinct (%)0.1%0.4%
Missing00
Missing (%)0.0%0.0%
Memory size10.8 KiB3.7 KiB
False
1233 
Yes
237 
ValueCountFrequency (%)
False 1233
100.0%
ValueCountFrequency (%)
Yes 237
100.0%

No Attrition

2023-05-20T15:43:57.696151image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:57.774836image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

BusinessTravel
Categorical

 No AttritionAttrition
Distinct33
Distinct (%)0.2%1.3%
Missing00
Missing (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
Travel_Rarely
887 
Travel_Frequently
208 
Non-Travel
138 
Travel_Rarely
156 
Travel_Frequently
69 
Non-Travel
 
12

Length

 No AttritionAttrition
Max length1717
Median length1313
Mean length13.33901114.012658
Min length1010

Characters and Unicode

 No AttritionAttrition
Total characters164473321
Distinct characters1717
Distinct categories44 ?
Distinct scripts22 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 No AttritionAttrition
Unique00 ?
Unique (%)0.0%0.0%

Sample

 No AttritionAttrition
1st rowTravel_FrequentlyTravel_Rarely
2nd rowTravel_FrequentlyTravel_Rarely
3rd rowTravel_RarelyTravel_Rarely
4th rowTravel_FrequentlyTravel_Rarely
5th rowTravel_RarelyTravel_Rarely

Common Values

ValueCountFrequency (%)
Travel_Rarely 887
71.9%
Travel_Frequently 208
 
16.9%
Non-Travel 138
 
11.2%
ValueCountFrequency (%)
Travel_Rarely 156
65.8%
Travel_Frequently 69
29.1%
Non-Travel 12
 
5.1%

Length

2023-05-20T15:43:57.851116image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

No Attrition

2023-05-20T15:43:57.960465image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:58.052862image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
travel_rarely 887
71.9%
travel_frequently 208
 
16.9%
non-travel 138
 
11.2%
ValueCountFrequency (%)
travel_rarely 156
65.8%
travel_frequently 69
29.1%
non-travel 12
 
5.1%

Most occurring characters

ValueCountFrequency (%)
e 2536
15.4%
r 2328
14.2%
l 2328
14.2%
a 2120
12.9%
T 1233
7.5%
v 1233
7.5%
y 1095
6.7%
_ 1095
6.7%
R 887
 
5.4%
n 346
 
2.1%
Other values (7) 1246
7.6%
ValueCountFrequency (%)
e 531
16.0%
r 462
13.9%
l 462
13.9%
a 393
11.8%
T 237
7.1%
v 237
7.1%
y 225
6.8%
_ 225
6.8%
R 156
 
4.7%
n 81
 
2.4%
Other values (7) 312
9.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12748
77.5%
Uppercase Letter 2466
 
15.0%
Connector Punctuation 1095
 
6.7%
Dash Punctuation 138
 
0.8%
ValueCountFrequency (%)
Lowercase Letter 2610
78.6%
Uppercase Letter 474
 
14.3%
Connector Punctuation 225
 
6.8%
Dash Punctuation 12
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2536
19.9%
r 2328
18.3%
l 2328
18.3%
a 2120
16.6%
v 1233
9.7%
y 1095
8.6%
n 346
 
2.7%
q 208
 
1.6%
u 208
 
1.6%
t 208
 
1.6%
ValueCountFrequency (%)
e 531
20.3%
r 462
17.7%
l 462
17.7%
a 393
15.1%
v 237
9.1%
y 225
8.6%
n 81
 
3.1%
q 69
 
2.6%
u 69
 
2.6%
t 69
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
T 1233
50.0%
R 887
36.0%
F 208
 
8.4%
N 138
 
5.6%
ValueCountFrequency (%)
T 237
50.0%
R 156
32.9%
F 69
 
14.6%
N 12
 
2.5%
Connector Punctuation
ValueCountFrequency (%)
_ 1095
100.0%
ValueCountFrequency (%)
_ 225
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 138
100.0%
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 15214
92.5%
Common 1233
 
7.5%
ValueCountFrequency (%)
Latin 3084
92.9%
Common 237
 
7.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2536
16.7%
r 2328
15.3%
l 2328
15.3%
a 2120
13.9%
T 1233
8.1%
v 1233
8.1%
y 1095
7.2%
R 887
 
5.8%
n 346
 
2.3%
F 208
 
1.4%
Other values (5) 900
 
5.9%
ValueCountFrequency (%)
e 531
17.2%
r 462
15.0%
l 462
15.0%
a 393
12.7%
T 237
7.7%
v 237
7.7%
y 225
7.3%
R 156
 
5.1%
n 81
 
2.6%
F 69
 
2.2%
Other values (5) 231
7.5%
Common
ValueCountFrequency (%)
_ 1095
88.8%
- 138
 
11.2%
ValueCountFrequency (%)
_ 225
94.9%
- 12
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16447
100.0%
ValueCountFrequency (%)
ASCII 3321
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 2536
15.4%
r 2328
14.2%
l 2328
14.2%
a 2120
12.9%
T 1233
7.5%
v 1233
7.5%
y 1095
6.7%
_ 1095
6.7%
R 887
 
5.4%
n 346
 
2.1%
Other values (7) 1246
7.6%
ValueCountFrequency (%)
e 531
16.0%
r 462
13.9%
l 462
13.9%
a 393
11.8%
T 237
7.1%
v 237
7.1%
y 225
6.8%
_ 225
6.8%
R 156
 
4.7%
n 81
 
2.4%
Other values (7) 312
9.4%

DailyRate
Real number (ℝ)

 No AttritionAttrition
Distinct802219
Distinct (%)65.0%92.4%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean812.50446750.36287
 No AttritionAttrition
Minimum102103
Maximum14991496
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
2023-05-20T15:43:58.181435image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

 No AttritionAttrition
Minimum102103
5-th percentile167154.2
Q1477408
median817699
Q311761092
95-th percentile1422.41428.4
Maximum14991496
Range13971393
Interquartile range (IQR)699684

Descriptive statistics

 No AttritionAttrition
Standard deviation403.20838401.89952
Coefficient of variation (CV)0.496253740.53560689
Kurtosis-1.1980717-1.1345978
Mean812.50446750.36287
Median Absolute Deviation (MAD)348339
Skewness-0.048657350.23415287
Sum1001818177836
Variance162577161523.22
MonotonicityNot monotonicNot monotonic
2023-05-20T15:43:58.353499image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
691 6
 
0.5%
1082 5
 
0.4%
1225 4
 
0.3%
1490 4
 
0.3%
829 4
 
0.3%
1469 4
 
0.3%
977 4
 
0.3%
430 4
 
0.3%
329 4
 
0.3%
1283 4
 
0.3%
Other values (792) 1190
96.5%
ValueCountFrequency (%)
1475 2
 
0.8%
289 2
 
0.8%
350 2
 
0.8%
303 2
 
0.8%
575 2
 
0.8%
240 2
 
0.8%
1362 2
 
0.8%
807 2
 
0.8%
337 2
 
0.8%
318 2
 
0.8%
Other values (209) 217
91.6%
ValueCountFrequency (%)
102 1
 
0.1%
105 1
 
0.1%
106 1
 
0.1%
107 1
 
0.1%
111 3
0.2%
116 2
0.2%
117 4
0.3%
118 1
 
0.1%
119 2
0.2%
120 2
0.2%
ValueCountFrequency (%)
103 1
0.4%
104 1
0.4%
109 1
0.4%
115 1
0.4%
118 1
0.4%
121 1
0.4%
129 1
0.4%
130 1
0.4%
135 1
0.4%
138 1
0.4%
ValueCountFrequency (%)
103 1
0.1%
104 1
0.1%
109 1
0.1%
115 1
0.1%
118 1
0.1%
121 1
0.1%
129 1
0.1%
130 1
0.1%
135 1
0.1%
138 1
0.1%
ValueCountFrequency (%)
102 1
 
0.4%
105 1
 
0.4%
106 1
 
0.4%
107 1
 
0.4%
111 3
1.3%
116 2
0.8%
117 4
1.7%
118 1
 
0.4%
119 2
0.8%
120 2
0.8%

Department
Categorical

 No AttritionAttrition
Distinct33
Distinct (%)0.2%1.3%
Missing00
Missing (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
Research & Development
828 
Sales
354 
Human Resources
 
51
Research & Development
133 
Sales
92 
Human Resources
 
12

Length

 No AttritionAttrition
Max length2222
Median length2222
Mean length16.82968415.046414
Min length55

Characters and Unicode

 No AttritionAttrition
Total characters207513566
Distinct characters2020
Distinct categories44 ?
Distinct scripts22 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 No AttritionAttrition
Unique00 ?
Unique (%)0.0%0.0%

Sample

 No AttritionAttrition
1st rowResearch & DevelopmentSales
2nd rowResearch & DevelopmentResearch & Development
3rd rowResearch & DevelopmentResearch & Development
4th rowResearch & DevelopmentSales
5th rowResearch & DevelopmentResearch & Development

Common Values

ValueCountFrequency (%)
Research & Development 828
67.2%
Sales 354
28.7%
Human Resources 51
 
4.1%
ValueCountFrequency (%)
Research & Development 133
56.1%
Sales 92
38.8%
Human Resources 12
 
5.1%

Length

2023-05-20T15:43:58.501301image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

No Attrition

2023-05-20T15:43:58.613667image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:58.696885image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
research 828
28.2%
828
28.2%
development 828
28.2%
sales 354
12.0%
human 51
 
1.7%
resources 51
 
1.7%
ValueCountFrequency (%)
research 133
25.8%
133
25.8%
development 133
25.8%
sales 92
17.9%
human 12
 
2.3%
resources 12
 
2.3%

Most occurring characters

ValueCountFrequency (%)
e 4596
22.1%
1707
 
8.2%
s 1284
 
6.2%
a 1233
 
5.9%
l 1182
 
5.7%
R 879
 
4.2%
r 879
 
4.2%
c 879
 
4.2%
n 879
 
4.2%
m 879
 
4.2%
Other values (10) 6354
30.6%
ValueCountFrequency (%)
e 781
21.9%
278
 
7.8%
s 249
 
7.0%
a 237
 
6.6%
l 225
 
6.3%
R 145
 
4.1%
r 145
 
4.1%
c 145
 
4.1%
n 145
 
4.1%
m 145
 
4.1%
Other values (10) 1071
30.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 16104
77.6%
Uppercase Letter 2112
 
10.2%
Space Separator 1707
 
8.2%
Other Punctuation 828
 
4.0%
ValueCountFrequency (%)
Lowercase Letter 2773
77.8%
Uppercase Letter 382
 
10.7%
Space Separator 278
 
7.8%
Other Punctuation 133
 
3.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4596
28.5%
s 1284
 
8.0%
a 1233
 
7.7%
l 1182
 
7.3%
r 879
 
5.5%
c 879
 
5.5%
n 879
 
5.5%
m 879
 
5.5%
o 879
 
5.5%
p 828
 
5.1%
Other values (4) 2586
16.1%
ValueCountFrequency (%)
e 781
28.2%
s 249
 
9.0%
a 237
 
8.5%
l 225
 
8.1%
r 145
 
5.2%
c 145
 
5.2%
n 145
 
5.2%
m 145
 
5.2%
o 145
 
5.2%
p 133
 
4.8%
Other values (4) 423
15.3%
Space Separator
ValueCountFrequency (%)
1707
100.0%
ValueCountFrequency (%)
278
100.0%
Uppercase Letter
ValueCountFrequency (%)
R 879
41.6%
D 828
39.2%
S 354
16.8%
H 51
 
2.4%
ValueCountFrequency (%)
R 145
38.0%
D 133
34.8%
S 92
24.1%
H 12
 
3.1%
Other Punctuation
ValueCountFrequency (%)
& 828
100.0%
ValueCountFrequency (%)
& 133
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 18216
87.8%
Common 2535
 
12.2%
ValueCountFrequency (%)
Latin 3155
88.5%
Common 411
 
11.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4596
25.2%
s 1284
 
7.0%
a 1233
 
6.8%
l 1182
 
6.5%
R 879
 
4.8%
r 879
 
4.8%
c 879
 
4.8%
n 879
 
4.8%
m 879
 
4.8%
o 879
 
4.8%
Other values (8) 4647
25.5%
ValueCountFrequency (%)
e 781
24.8%
s 249
 
7.9%
a 237
 
7.5%
l 225
 
7.1%
R 145
 
4.6%
r 145
 
4.6%
c 145
 
4.6%
n 145
 
4.6%
m 145
 
4.6%
o 145
 
4.6%
Other values (8) 793
25.1%
Common
ValueCountFrequency (%)
1707
67.3%
& 828
32.7%
ValueCountFrequency (%)
278
67.6%
& 133
32.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20751
100.0%
ValueCountFrequency (%)
ASCII 3566
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 4596
22.1%
1707
 
8.2%
s 1284
 
6.2%
a 1233
 
5.9%
l 1182
 
5.7%
R 879
 
4.2%
r 879
 
4.2%
c 879
 
4.2%
n 879
 
4.2%
m 879
 
4.2%
Other values (10) 6354
30.6%
ValueCountFrequency (%)
e 781
21.9%
278
 
7.8%
s 249
 
7.0%
a 237
 
6.6%
l 225
 
6.3%
R 145
 
4.1%
r 145
 
4.1%
c 145
 
4.1%
n 145
 
4.1%
m 145
 
4.1%
Other values (10) 1071
30.0%

DistanceFromHome
Real number (ℝ)

 No AttritionAttrition
Distinct2929
Distinct (%)2.4%12.2%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean8.915652910.632911
 No AttritionAttrition
Minimum11
Maximum2929
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
2023-05-20T15:43:58.806233image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

 No AttritionAttrition
Minimum11
5-th percentile11
Q123
median79
Q31317
95-th percentile2626
Maximum2929
Range2828
Interquartile range (IQR)1114

Descriptive statistics

 No AttritionAttrition
Standard deviation8.01263358.4525253
Coefficient of variation (CV)0.898715280.79493988
Kurtosis-0.044353391-0.86030637
Mean8.915652910.632911
Median Absolute Deviation (MAD)57
Skewness1.02910560.63590333
Sum109932520
Variance64.20229571.445183
MonotonicityNot monotonicNot monotonic
2023-05-20T15:43:58.935404image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
2 183
14.8%
1 182
14.8%
10 75
 
6.1%
7 73
 
5.9%
3 70
 
5.7%
8 70
 
5.7%
9 67
 
5.4%
4 55
 
4.5%
5 55
 
4.5%
6 52
 
4.2%
Other values (19) 351
28.5%
ValueCountFrequency (%)
2 28
 
11.8%
1 26
 
11.0%
9 18
 
7.6%
3 14
 
5.9%
24 12
 
5.1%
10 11
 
4.6%
7 11
 
4.6%
5 10
 
4.2%
8 10
 
4.2%
4 9
 
3.8%
Other values (19) 88
37.1%
ValueCountFrequency (%)
1 182
14.8%
2 183
14.8%
3 70
 
5.7%
4 55
 
4.5%
5 55
 
4.5%
6 52
 
4.2%
7 73
 
5.9%
8 70
 
5.7%
9 67
 
5.4%
10 75
6.1%
ValueCountFrequency (%)
1 26
11.0%
2 28
11.8%
3 14
5.9%
4 9
 
3.8%
5 10
 
4.2%
6 7
 
3.0%
7 11
 
4.6%
8 10
 
4.2%
9 18
7.6%
10 11
 
4.6%
ValueCountFrequency (%)
1 26
2.1%
2 28
2.3%
3 14
1.1%
4 9
 
0.7%
5 10
 
0.8%
6 7
 
0.6%
7 11
 
0.9%
8 10
 
0.8%
9 18
1.5%
10 11
 
0.9%
ValueCountFrequency (%)
1 182
76.8%
2 183
77.2%
3 70
 
29.5%
4 55
 
23.2%
5 55
 
23.2%
6 52
 
21.9%
7 73
 
30.8%
8 70
 
29.5%
9 67
 
28.3%
10 75
31.6%

Education
Categorical

 No AttritionAttrition
Distinct55
Distinct (%)0.4%2.1%
Missing00
Missing (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
3
473 
4
340 
2
238 
1
139 
5
 
43
3
99 
4
58 
2
44 
1
31 
5
 
5

Length

 No AttritionAttrition
Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

 No AttritionAttrition
Total characters1233237
Distinct characters55
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 No AttritionAttrition
Unique00 ?
Unique (%)0.0%0.0%

Sample

 No AttritionAttrition
1st row12
2nd row42
3rd row13
4th row24
5th row31

Common Values

ValueCountFrequency (%)
3 473
38.4%
4 340
27.6%
2 238
19.3%
1 139
 
11.3%
5 43
 
3.5%
ValueCountFrequency (%)
3 99
41.8%
4 58
24.5%
2 44
18.6%
1 31
 
13.1%
5 5
 
2.1%

Length

2023-05-20T15:43:59.053513image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

No Attrition

2023-05-20T15:43:59.165909image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:59.259635image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
3 473
38.4%
4 340
27.6%
2 238
19.3%
1 139
 
11.3%
5 43
 
3.5%
ValueCountFrequency (%)
3 99
41.8%
4 58
24.5%
2 44
18.6%
1 31
 
13.1%
5 5
 
2.1%

Most occurring characters

ValueCountFrequency (%)
3 473
38.4%
4 340
27.6%
2 238
19.3%
1 139
 
11.3%
5 43
 
3.5%
ValueCountFrequency (%)
3 99
41.8%
4 58
24.5%
2 44
18.6%
1 31
 
13.1%
5 5
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1233
100.0%
ValueCountFrequency (%)
Decimal Number 237
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 473
38.4%
4 340
27.6%
2 238
19.3%
1 139
 
11.3%
5 43
 
3.5%
ValueCountFrequency (%)
3 99
41.8%
4 58
24.5%
2 44
18.6%
1 31
 
13.1%
5 5
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1233
100.0%
ValueCountFrequency (%)
Common 237
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 473
38.4%
4 340
27.6%
2 238
19.3%
1 139
 
11.3%
5 43
 
3.5%
ValueCountFrequency (%)
3 99
41.8%
4 58
24.5%
2 44
18.6%
1 31
 
13.1%
5 5
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1233
100.0%
ValueCountFrequency (%)
ASCII 237
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 473
38.4%
4 340
27.6%
2 238
19.3%
1 139
 
11.3%
5 43
 
3.5%
ValueCountFrequency (%)
3 99
41.8%
4 58
24.5%
2 44
18.6%
1 31
 
13.1%
5 5
 
2.1%

EducationField
Categorical

 No AttritionAttrition
Distinct66
Distinct (%)0.5%2.5%
Missing00
Missing (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
Life Sciences
517 
Medical
401 
Marketing
124 
Technical Degree
100 
Other
71 
Life Sciences
89 
Medical
63 
Marketing
35 
Technical Degree
32 
Other
11 

Length

 No AttritionAttrition
Max length1616
Median length1515
Mean length10.46147610.907173
Min length55

Characters and Unicode

 No AttritionAttrition
Total characters128992585
Distinct characters2626
Distinct categories33 ?
Distinct scripts22 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 No AttritionAttrition
Unique00 ?
Unique (%)0.0%0.0%

Sample

 No AttritionAttrition
1st rowLife SciencesLife Sciences
2nd rowLife SciencesOther
3rd rowMedicalLife Sciences
4th rowLife SciencesLife Sciences
5th rowMedicalMedical

Common Values

ValueCountFrequency (%)
Life Sciences 517
41.9%
Medical 401
32.5%
Marketing 124
 
10.1%
Technical Degree 100
 
8.1%
Other 71
 
5.8%
Human Resources 20
 
1.6%
ValueCountFrequency (%)
Life Sciences 89
37.6%
Medical 63
26.6%
Marketing 35
 
14.8%
Technical Degree 32
 
13.5%
Other 11
 
4.6%
Human Resources 7
 
3.0%

Length

2023-05-20T15:43:59.375746image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

No Attrition

2023-05-20T15:43:59.492481image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:59.613191image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
life 517
27.6%
sciences 517
27.6%
medical 401
21.4%
marketing 124
 
6.6%
technical 100
 
5.3%
degree 100
 
5.3%
other 71
 
3.8%
human 20
 
1.1%
resources 20
 
1.1%
ValueCountFrequency (%)
life 89
24.4%
sciences 89
24.4%
medical 63
17.3%
marketing 35
 
9.6%
technical 32
 
8.8%
degree 32
 
8.8%
other 11
 
3.0%
human 7
 
1.9%
resources 7
 
1.9%

Most occurring characters

ValueCountFrequency (%)
e 2587
20.1%
i 1659
12.9%
c 1655
12.8%
n 761
 
5.9%
a 645
 
5.0%
637
 
4.9%
s 557
 
4.3%
M 525
 
4.1%
L 517
 
4.0%
f 517
 
4.0%
Other values (16) 2839
22.0%
ValueCountFrequency (%)
e 518
20.0%
c 312
12.1%
i 308
11.9%
n 163
 
6.3%
a 137
 
5.3%
128
 
5.0%
s 103
 
4.0%
M 98
 
3.8%
l 95
 
3.7%
L 89
 
3.4%
Other values (16) 634
24.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10392
80.6%
Uppercase Letter 1870
 
14.5%
Space Separator 637
 
4.9%
ValueCountFrequency (%)
Lowercase Letter 2092
80.9%
Uppercase Letter 365
 
14.1%
Space Separator 128
 
5.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2587
24.9%
i 1659
16.0%
c 1655
15.9%
n 761
 
7.3%
a 645
 
6.2%
s 557
 
5.4%
f 517
 
5.0%
l 501
 
4.8%
d 401
 
3.9%
r 315
 
3.0%
Other values (7) 794
 
7.6%
ValueCountFrequency (%)
e 518
24.8%
c 312
14.9%
i 308
14.7%
n 163
 
7.8%
a 137
 
6.5%
s 103
 
4.9%
l 95
 
4.5%
f 89
 
4.3%
r 85
 
4.1%
g 67
 
3.2%
Other values (7) 215
10.3%
Space Separator
ValueCountFrequency (%)
637
100.0%
ValueCountFrequency (%)
128
100.0%
Uppercase Letter
ValueCountFrequency (%)
M 525
28.1%
L 517
27.6%
S 517
27.6%
T 100
 
5.3%
D 100
 
5.3%
O 71
 
3.8%
H 20
 
1.1%
R 20
 
1.1%
ValueCountFrequency (%)
M 98
26.8%
L 89
24.4%
S 89
24.4%
T 32
 
8.8%
D 32
 
8.8%
O 11
 
3.0%
H 7
 
1.9%
R 7
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 12262
95.1%
Common 637
 
4.9%
ValueCountFrequency (%)
Latin 2457
95.0%
Common 128
 
5.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2587
21.1%
i 1659
13.5%
c 1655
13.5%
n 761
 
6.2%
a 645
 
5.3%
s 557
 
4.5%
M 525
 
4.3%
L 517
 
4.2%
f 517
 
4.2%
S 517
 
4.2%
Other values (15) 2322
18.9%
ValueCountFrequency (%)
e 518
21.1%
c 312
12.7%
i 308
12.5%
n 163
 
6.6%
a 137
 
5.6%
s 103
 
4.2%
M 98
 
4.0%
l 95
 
3.9%
L 89
 
3.6%
f 89
 
3.6%
Other values (15) 545
22.2%
Common
ValueCountFrequency (%)
637
100.0%
ValueCountFrequency (%)
128
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12899
100.0%
ValueCountFrequency (%)
ASCII 2585
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 2587
20.1%
i 1659
12.9%
c 1655
12.8%
n 761
 
5.9%
a 645
 
5.0%
637
 
4.9%
s 557
 
4.3%
M 525
 
4.1%
L 517
 
4.0%
f 517
 
4.0%
Other values (16) 2839
22.0%
ValueCountFrequency (%)
e 518
20.0%
c 312
12.1%
i 308
11.9%
n 163
 
6.3%
a 137
 
5.3%
128
 
5.0%
s 103
 
4.0%
M 98
 
3.8%
l 95
 
3.7%
L 89
 
3.4%
Other values (16) 634
24.5%

EmployeeCount
Categorical

 No AttritionAttrition
Distinct11
Distinct (%)0.1%0.4%
Missing00
Missing (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
1
1233 
1
237 

Length

 No AttritionAttrition
Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

 No AttritionAttrition
Total characters1233237
Distinct characters11
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 No AttritionAttrition
Unique00 ?
Unique (%)0.0%0.0%

Sample

 No AttritionAttrition
1st row11
2nd row11
3rd row11
4th row11
5th row11

Common Values

ValueCountFrequency (%)
1 1233
100.0%
ValueCountFrequency (%)
1 237
100.0%

Length

2023-05-20T15:43:59.713365image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

No Attrition

2023-05-20T15:43:59.807093image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:59.869576image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
1 1233
100.0%
ValueCountFrequency (%)
1 237
100.0%

Most occurring characters

ValueCountFrequency (%)
1 1233
100.0%
ValueCountFrequency (%)
1 237
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1233
100.0%
ValueCountFrequency (%)
Decimal Number 237
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1233
100.0%
ValueCountFrequency (%)
1 237
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1233
100.0%
ValueCountFrequency (%)
Common 237
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1233
100.0%
ValueCountFrequency (%)
1 237
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1233
100.0%
ValueCountFrequency (%)
ASCII 237
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1233
100.0%
ValueCountFrequency (%)
1 237
100.0%

EmployeeNumber
Real number (ℝ)

 No AttritionAttrition
Distinct1233237
Distinct (%)100.0%100.0%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean1027.65611010.346
 No AttritionAttrition
Minimum21
Maximum20682055
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
2023-05-20T15:44:00.007385image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

 No AttritionAttrition
Minimum21
5-th percentile99.264.8
Q1483514
median10221017
Q315741486
95-th percentile1974.41911.2
Maximum20682055
Range20662054
Interquartile range (IQR)1091972

Descriptive statistics

 No AttritionAttrition
Standard deviation606.21707580.75057
Coefficient of variation (CV)0.589902650.57480366
Kurtosis-1.2438438-1.1114959
Mean1027.65611010.346
Median Absolute Deviation (MAD)542472
Skewness0.020213347-0.012146585
Sum1267100239452
Variance367499.14337271.23
MonotonicityStrictly increasingStrictly increasing
2023-05-20T15:44:00.168446image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 1
 
0.1%
1390 1
 
0.1%
1399 1
 
0.1%
1397 1
 
0.1%
1396 1
 
0.1%
1395 1
 
0.1%
1394 1
 
0.1%
1392 1
 
0.1%
1391 1
 
0.1%
1387 1
 
0.1%
Other values (1223) 1223
99.2%
ValueCountFrequency (%)
1 1
 
0.4%
1379 1
 
0.4%
1277 1
 
0.4%
1279 1
 
0.4%
1295 1
 
0.4%
1299 1
 
0.4%
1309 1
 
0.4%
1310 1
 
0.4%
1318 1
 
0.4%
1319 1
 
0.4%
Other values (227) 227
95.8%
ValueCountFrequency (%)
2 1
0.1%
5 1
0.1%
7 1
0.1%
8 1
0.1%
10 1
0.1%
11 1
0.1%
12 1
0.1%
13 1
0.1%
14 1
0.1%
15 1
0.1%
ValueCountFrequency (%)
1 1
0.4%
4 1
0.4%
19 1
0.4%
27 1
0.4%
31 1
0.4%
33 1
0.4%
42 1
0.4%
45 1
0.4%
47 1
0.4%
55 1
0.4%
ValueCountFrequency (%)
1 1
0.1%
4 1
0.1%
19 1
0.1%
27 1
0.1%
31 1
0.1%
33 1
0.1%
42 1
0.1%
45 1
0.1%
47 1
0.1%
55 1
0.1%
ValueCountFrequency (%)
2 1
0.4%
5 1
0.4%
7 1
0.4%
8 1
0.4%
10 1
0.4%
11 1
0.4%
12 1
0.4%
13 1
0.4%
14 1
0.4%
15 1
0.4%

EnvironmentSatisfaction
Categorical

 No AttritionAttrition
Distinct44
Distinct (%)0.3%1.7%
Missing00
Missing (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
3
391 
4
386 
2
244 
1
212 
1
72 
3
62 
4
60 
2
43 

Length

 No AttritionAttrition
Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

 No AttritionAttrition
Total characters1233237
Distinct characters44
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 No AttritionAttrition
Unique00 ?
Unique (%)0.0%0.0%

Sample

 No AttritionAttrition
1st row32
2nd row44
3rd row13
4th row43
5th row32

Common Values

ValueCountFrequency (%)
3 391
31.7%
4 386
31.3%
2 244
19.8%
1 212
17.2%
ValueCountFrequency (%)
1 72
30.4%
3 62
26.2%
4 60
25.3%
2 43
18.1%

Length

2023-05-20T15:44:00.402730image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

No Attrition

2023-05-20T15:44:00.508002image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:44:00.607961image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
3 391
31.7%
4 386
31.3%
2 244
19.8%
1 212
17.2%
ValueCountFrequency (%)
1 72
30.4%
3 62
26.2%
4 60
25.3%
2 43
18.1%

Most occurring characters

ValueCountFrequency (%)
3 391
31.7%
4 386
31.3%
2 244
19.8%
1 212
17.2%
ValueCountFrequency (%)
1 72
30.4%
3 62
26.2%
4 60
25.3%
2 43
18.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1233
100.0%
ValueCountFrequency (%)
Decimal Number 237
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 391
31.7%
4 386
31.3%
2 244
19.8%
1 212
17.2%
ValueCountFrequency (%)
1 72
30.4%
3 62
26.2%
4 60
25.3%
2 43
18.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1233
100.0%
ValueCountFrequency (%)
Common 237
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 391
31.7%
4 386
31.3%
2 244
19.8%
1 212
17.2%
ValueCountFrequency (%)
1 72
30.4%
3 62
26.2%
4 60
25.3%
2 43
18.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1233
100.0%
ValueCountFrequency (%)
ASCII 237
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 391
31.7%
4 386
31.3%
2 244
19.8%
1 212
17.2%
ValueCountFrequency (%)
1 72
30.4%
3 62
26.2%
4 60
25.3%
2 43
18.1%

Gender
Categorical

 No AttritionAttrition
Distinct22
Distinct (%)0.2%0.8%
Missing00
Missing (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
Male
732 
Female
501 
Male
150 
Female
87 

Length

 No AttritionAttrition
Max length66
Median length44
Mean length4.81265214.7341772
Min length44

Characters and Unicode

 No AttritionAttrition
Total characters59341122
Distinct characters66
Distinct categories22 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 No AttritionAttrition
Unique00 ?
Unique (%)0.0%0.0%

Sample

 No AttritionAttrition
1st rowMaleFemale
2nd rowFemaleMale
3rd rowMaleMale
4th rowMaleMale
5th rowFemaleMale

Common Values

ValueCountFrequency (%)
Male 732
59.4%
Female 501
40.6%
ValueCountFrequency (%)
Male 150
63.3%
Female 87
36.7%

Length

2023-05-20T15:44:00.699704image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

No Attrition

2023-05-20T15:44:00.809051image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:44:00.902782image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
male 732
59.4%
female 501
40.6%
ValueCountFrequency (%)
male 150
63.3%
female 87
36.7%

Most occurring characters

ValueCountFrequency (%)
e 1734
29.2%
a 1233
20.8%
l 1233
20.8%
M 732
12.3%
F 501
 
8.4%
m 501
 
8.4%
ValueCountFrequency (%)
e 324
28.9%
a 237
21.1%
l 237
21.1%
M 150
13.4%
F 87
 
7.8%
m 87
 
7.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4701
79.2%
Uppercase Letter 1233
 
20.8%
ValueCountFrequency (%)
Lowercase Letter 885
78.9%
Uppercase Letter 237
 
21.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1734
36.9%
a 1233
26.2%
l 1233
26.2%
m 501
 
10.7%
ValueCountFrequency (%)
e 324
36.6%
a 237
26.8%
l 237
26.8%
m 87
 
9.8%
Uppercase Letter
ValueCountFrequency (%)
M 732
59.4%
F 501
40.6%
ValueCountFrequency (%)
M 150
63.3%
F 87
36.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 5934
100.0%
ValueCountFrequency (%)
Latin 1122
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1734
29.2%
a 1233
20.8%
l 1233
20.8%
M 732
12.3%
F 501
 
8.4%
m 501
 
8.4%
ValueCountFrequency (%)
e 324
28.9%
a 237
21.1%
l 237
21.1%
M 150
13.4%
F 87
 
7.8%
m 87
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5934
100.0%
ValueCountFrequency (%)
ASCII 1122
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1734
29.2%
a 1233
20.8%
l 1233
20.8%
M 732
12.3%
F 501
 
8.4%
m 501
 
8.4%
ValueCountFrequency (%)
e 324
28.9%
a 237
21.1%
l 237
21.1%
M 150
13.4%
F 87
 
7.8%
m 87
 
7.8%

HourlyRate
Real number (ℝ)

 No AttritionAttrition
Distinct7169
Distinct (%)5.8%29.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean65.95214965.57384
 No AttritionAttrition
Minimum3031
Maximum100100
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
2023-05-20T15:44:01.023501image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

 No AttritionAttrition
Minimum3031
5-th percentile3334
Q14850
median6666
Q38384
95-th percentile9797.2
Maximum100100
Range7069
Interquartile range (IQR)3534

Descriptive statistics

 No AttritionAttrition
Standard deviation20.38075420.099958
Coefficient of variation (CV)0.309023350.30652403
Kurtosis-1.2034901-1.1520236
Mean65.95214965.57384
Median Absolute Deviation (MAD)1817
Skewness-0.0479544730.051688955
Sum8131915541
Variance415.37514404.0083
MonotonicityNot monotonicNot monotonic
2023-05-20T15:44:01.199348image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42 28
 
2.3%
98 25
 
2.0%
87 25
 
2.0%
96 23
 
1.9%
48 23
 
1.9%
92 22
 
1.8%
56 22
 
1.8%
84 22
 
1.8%
66 22
 
1.8%
60 21
 
1.7%
Other values (61) 1000
81.1%
ValueCountFrequency (%)
66 7
 
3.0%
50 6
 
2.5%
57 6
 
2.5%
84 6
 
2.5%
85 6
 
2.5%
79 6
 
2.5%
70 6
 
2.5%
94 5
 
2.1%
100 5
 
2.1%
51 5
 
2.1%
Other values (59) 179
75.5%
ValueCountFrequency (%)
30 19
1.5%
31 13
1.1%
32 20
1.6%
33 16
1.3%
34 7
 
0.6%
35 17
1.4%
36 13
1.1%
37 15
1.2%
38 9
0.7%
39 13
1.1%
ValueCountFrequency (%)
31 2
 
0.8%
32 4
1.7%
33 3
1.3%
34 5
2.1%
35 1
 
0.4%
36 5
2.1%
37 3
1.3%
38 4
1.7%
39 4
1.7%
40 2
 
0.8%
ValueCountFrequency (%)
31 2
 
0.2%
32 4
0.3%
33 3
0.2%
34 5
0.4%
35 1
 
0.1%
36 5
0.4%
37 3
0.2%
38 4
0.3%
39 4
0.3%
40 2
 
0.2%
ValueCountFrequency (%)
30 19
8.0%
31 13
5.5%
32 20
8.4%
33 16
6.8%
34 7
 
3.0%
35 17
7.2%
36 13
5.5%
37 15
6.3%
38 9
3.8%
39 13
5.5%

JobInvolvement
Categorical

 No AttritionAttrition
Distinct44
Distinct (%)0.3%1.7%
Missing00
Missing (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
3
743 
2
304 
4
131 
1
 
55
3
125 
2
71 
1
28 
4
13 

Length

 No AttritionAttrition
Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

 No AttritionAttrition
Total characters1233237
Distinct characters44
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 No AttritionAttrition
Unique00 ?
Unique (%)0.0%0.0%

Sample

 No AttritionAttrition
1st row23
2nd row32
3rd row32
4th row32
5th row43

Common Values

ValueCountFrequency (%)
3 743
60.3%
2 304
24.7%
4 131
 
10.6%
1 55
 
4.5%
ValueCountFrequency (%)
3 125
52.7%
2 71
30.0%
1 28
 
11.8%
4 13
 
5.5%

Length

2023-05-20T15:44:01.324313image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

No Attrition

2023-05-20T15:44:01.433662image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:44:01.523087image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
3 743
60.3%
2 304
24.7%
4 131
 
10.6%
1 55
 
4.5%
ValueCountFrequency (%)
3 125
52.7%
2 71
30.0%
1 28
 
11.8%
4 13
 
5.5%

Most occurring characters

ValueCountFrequency (%)
3 743
60.3%
2 304
24.7%
4 131
 
10.6%
1 55
 
4.5%
ValueCountFrequency (%)
3 125
52.7%
2 71
30.0%
1 28
 
11.8%
4 13
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1233
100.0%
ValueCountFrequency (%)
Decimal Number 237
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 743
60.3%
2 304
24.7%
4 131
 
10.6%
1 55
 
4.5%
ValueCountFrequency (%)
3 125
52.7%
2 71
30.0%
1 28
 
11.8%
4 13
 
5.5%

Most occurring scripts

ValueCountFrequency (%)
Common 1233
100.0%
ValueCountFrequency (%)
Common 237
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 743
60.3%
2 304
24.7%
4 131
 
10.6%
1 55
 
4.5%
ValueCountFrequency (%)
3 125
52.7%
2 71
30.0%
1 28
 
11.8%
4 13
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1233
100.0%
ValueCountFrequency (%)
ASCII 237
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 743
60.3%
2 304
24.7%
4 131
 
10.6%
1 55
 
4.5%
ValueCountFrequency (%)
3 125
52.7%
2 71
30.0%
1 28
 
11.8%
4 13
 
5.5%

JobLevel
Categorical

 No AttritionAttrition
Distinct55
Distinct (%)0.4%2.1%
Missing00
Missing (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
2
482 
1
400 
3
186 
4
101 
5
64 
1
143 
2
52 
3
32 
5
 
5
4
 
5

Length

 No AttritionAttrition
Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

 No AttritionAttrition
Total characters1233237
Distinct characters55
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 No AttritionAttrition
Unique00 ?
Unique (%)0.0%0.0%

Sample

 No AttritionAttrition
1st row22
2nd row11
3rd row11
4th row11
5th row11

Common Values

ValueCountFrequency (%)
2 482
39.1%
1 400
32.4%
3 186
 
15.1%
4 101
 
8.2%
5 64
 
5.2%
ValueCountFrequency (%)
1 143
60.3%
2 52
 
21.9%
3 32
 
13.5%
5 5
 
2.1%
4 5
 
2.1%

Length

2023-05-20T15:44:01.616822image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

No Attrition

2023-05-20T15:44:01.716605image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:44:01.825954image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
2 482
39.1%
1 400
32.4%
3 186
 
15.1%
4 101
 
8.2%
5 64
 
5.2%
ValueCountFrequency (%)
1 143
60.3%
2 52
 
21.9%
3 32
 
13.5%
5 5
 
2.1%
4 5
 
2.1%

Most occurring characters

ValueCountFrequency (%)
2 482
39.1%
1 400
32.4%
3 186
 
15.1%
4 101
 
8.2%
5 64
 
5.2%
ValueCountFrequency (%)
1 143
60.3%
2 52
 
21.9%
3 32
 
13.5%
5 5
 
2.1%
4 5
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1233
100.0%
ValueCountFrequency (%)
Decimal Number 237
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 482
39.1%
1 400
32.4%
3 186
 
15.1%
4 101
 
8.2%
5 64
 
5.2%
ValueCountFrequency (%)
1 143
60.3%
2 52
 
21.9%
3 32
 
13.5%
5 5
 
2.1%
4 5
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1233
100.0%
ValueCountFrequency (%)
Common 237
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 482
39.1%
1 400
32.4%
3 186
 
15.1%
4 101
 
8.2%
5 64
 
5.2%
ValueCountFrequency (%)
1 143
60.3%
2 52
 
21.9%
3 32
 
13.5%
5 5
 
2.1%
4 5
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1233
100.0%
ValueCountFrequency (%)
ASCII 237
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 482
39.1%
1 400
32.4%
3 186
 
15.1%
4 101
 
8.2%
5 64
 
5.2%
ValueCountFrequency (%)
1 143
60.3%
2 52
 
21.9%
3 32
 
13.5%
5 5
 
2.1%
4 5
 
2.1%

JobRole
Categorical

 No AttritionAttrition
Distinct99
Distinct (%)0.7%3.8%
Missing00
Missing (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
Sales Executive
269 
Research Scientist
245 
Laboratory Technician
197 
Manufacturing Director
135 
Healthcare Representative
122 
Other values (4)
265 
Laboratory Technician
62 
Sales Executive
57 
Research Scientist
47 
Sales Representative
33 
Human Resources
12 
Other values (4)
26 

Length

 No AttritionAttrition
Max length2525
Median length2122
Mean length18.01054318.383966
Min length77

Characters and Unicode

 No AttritionAttrition
Total characters222074357
Distinct characters2929
Distinct categories33 ?
Distinct scripts22 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 No AttritionAttrition
Unique00 ?
Unique (%)0.0%0.0%

Sample

 No AttritionAttrition
1st rowResearch ScientistSales Executive
2nd rowResearch ScientistLaboratory Technician
3rd rowLaboratory TechnicianLaboratory Technician
4th rowLaboratory TechnicianSales Representative
5th rowLaboratory TechnicianResearch Scientist

Common Values

ValueCountFrequency (%)
Sales Executive 269
21.8%
Research Scientist 245
19.9%
Laboratory Technician 197
16.0%
Manufacturing Director 135
10.9%
Healthcare Representative 122
9.9%
Manager 97
 
7.9%
Research Director 78
 
6.3%
Sales Representative 50
 
4.1%
Human Resources 40
 
3.2%
ValueCountFrequency (%)
Laboratory Technician 62
26.2%
Sales Executive 57
24.1%
Research Scientist 47
19.8%
Sales Representative 33
13.9%
Human Resources 12
 
5.1%
Manufacturing Director 10
 
4.2%
Healthcare Representative 9
 
3.8%
Manager 5
 
2.1%
Research Director 2
 
0.8%

Length

2023-05-20T15:44:01.935303image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

No Attrition

2023-05-20T15:44:02.074669image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:44:02.247424image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
research 323
13.6%
sales 319
13.5%
executive 269
11.4%
scientist 245
10.3%
director 213
9.0%
laboratory 197
8.3%
technician 197
8.3%
representative 172
7.3%
manufacturing 135
5.7%
healthcare 122
 
5.1%
Other values (3) 177
7.5%
ValueCountFrequency (%)
sales 90
19.2%
laboratory 62
13.2%
technician 62
13.2%
executive 57
12.2%
research 49
10.4%
scientist 47
10.0%
representative 42
9.0%
human 12
 
2.6%
resources 12
 
2.6%
director 12
 
2.6%
Other values (3) 24
 
5.1%

Most occurring characters

ValueCountFrequency (%)
e 3267
14.7%
a 2153
 
9.7%
t 1770
 
8.0%
c 1741
 
7.8%
r 1709
 
7.7%
i 1673
 
7.5%
n 1218
 
5.5%
s 1139
 
5.1%
1136
 
5.1%
o 647
 
2.9%
Other values (19) 5754
25.9%
ValueCountFrequency (%)
e 638
14.6%
a 427
 
9.8%
i 339
 
7.8%
t 328
 
7.5%
c 320
 
7.3%
r 275
 
6.3%
s 252
 
5.8%
n 250
 
5.7%
232
 
5.3%
o 148
 
3.4%
Other values (19) 1148
26.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 18702
84.2%
Uppercase Letter 2369
 
10.7%
Space Separator 1136
 
5.1%
ValueCountFrequency (%)
Lowercase Letter 3656
83.9%
Uppercase Letter 469
 
10.8%
Space Separator 232
 
5.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 3267
17.5%
a 2153
11.5%
t 1770
9.5%
c 1741
9.3%
r 1709
9.1%
i 1673
8.9%
n 1218
 
6.5%
s 1139
 
6.1%
o 647
 
3.5%
h 642
 
3.4%
Other values (10) 2743
14.7%
ValueCountFrequency (%)
e 638
17.5%
a 427
11.7%
i 339
9.3%
t 328
9.0%
c 320
8.8%
r 275
7.5%
s 252
 
6.9%
n 250
 
6.8%
o 148
 
4.0%
h 120
 
3.3%
Other values (10) 559
15.3%
Space Separator
ValueCountFrequency (%)
1136
100.0%
ValueCountFrequency (%)
232
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 564
23.8%
R 535
22.6%
E 269
11.4%
M 232
9.8%
D 213
 
9.0%
L 197
 
8.3%
T 197
 
8.3%
H 162
 
6.8%
ValueCountFrequency (%)
S 137
29.2%
R 103
22.0%
L 62
13.2%
T 62
13.2%
E 57
12.2%
H 21
 
4.5%
M 15
 
3.2%
D 12
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 21071
94.9%
Common 1136
 
5.1%
ValueCountFrequency (%)
Latin 4125
94.7%
Common 232
 
5.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3267
15.5%
a 2153
10.2%
t 1770
 
8.4%
c 1741
 
8.3%
r 1709
 
8.1%
i 1673
 
7.9%
n 1218
 
5.8%
s 1139
 
5.4%
o 647
 
3.1%
h 642
 
3.0%
Other values (18) 5112
24.3%
ValueCountFrequency (%)
e 638
15.5%
a 427
10.4%
i 339
 
8.2%
t 328
 
8.0%
c 320
 
7.8%
r 275
 
6.7%
s 252
 
6.1%
n 250
 
6.1%
o 148
 
3.6%
S 137
 
3.3%
Other values (18) 1011
24.5%
Common
ValueCountFrequency (%)
1136
100.0%
ValueCountFrequency (%)
232
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22207
100.0%
ValueCountFrequency (%)
ASCII 4357
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 3267
14.7%
a 2153
 
9.7%
t 1770
 
8.0%
c 1741
 
7.8%
r 1709
 
7.7%
i 1673
 
7.5%
n 1218
 
5.5%
s 1139
 
5.1%
1136
 
5.1%
o 647
 
2.9%
Other values (19) 5754
25.9%
ValueCountFrequency (%)
e 638
14.6%
a 427
 
9.8%
i 339
 
7.8%
t 328
 
7.5%
c 320
 
7.3%
r 275
 
6.3%
s 252
 
5.8%
n 250
 
5.7%
232
 
5.3%
o 148
 
3.4%
Other values (19) 1148
26.3%

JobSatisfaction
Categorical

 No AttritionAttrition
Distinct44
Distinct (%)0.3%1.7%
Missing00
Missing (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
4
407 
3
369 
2
234 
1
223 
3
73 
1
66 
4
52 
2
46 

Length

 No AttritionAttrition
Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

 No AttritionAttrition
Total characters1233237
Distinct characters44
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 No AttritionAttrition
Unique00 ?
Unique (%)0.0%0.0%

Sample

 No AttritionAttrition
1st row24
2nd row33
3rd row23
4th row41
5th row11

Common Values

ValueCountFrequency (%)
4 407
33.0%
3 369
29.9%
2 234
19.0%
1 223
18.1%
ValueCountFrequency (%)
3 73
30.8%
1 66
27.8%
4 52
21.9%
2 46
19.4%

Length

2023-05-20T15:44:02.372396image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

No Attrition

2023-05-20T15:44:02.486940image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:44:02.590777image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
4 407
33.0%
3 369
29.9%
2 234
19.0%
1 223
18.1%
ValueCountFrequency (%)
3 73
30.8%
1 66
27.8%
4 52
21.9%
2 46
19.4%

Most occurring characters

ValueCountFrequency (%)
4 407
33.0%
3 369
29.9%
2 234
19.0%
1 223
18.1%
ValueCountFrequency (%)
3 73
30.8%
1 66
27.8%
4 52
21.9%
2 46
19.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1233
100.0%
ValueCountFrequency (%)
Decimal Number 237
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 407
33.0%
3 369
29.9%
2 234
19.0%
1 223
18.1%
ValueCountFrequency (%)
3 73
30.8%
1 66
27.8%
4 52
21.9%
2 46
19.4%

Most occurring scripts

ValueCountFrequency (%)
Common 1233
100.0%
ValueCountFrequency (%)
Common 237
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 407
33.0%
3 369
29.9%
2 234
19.0%
1 223
18.1%
ValueCountFrequency (%)
3 73
30.8%
1 66
27.8%
4 52
21.9%
2 46
19.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1233
100.0%
ValueCountFrequency (%)
ASCII 237
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 407
33.0%
3 369
29.9%
2 234
19.0%
1 223
18.1%
ValueCountFrequency (%)
3 73
30.8%
1 66
27.8%
4 52
21.9%
2 46
19.4%

MaritalStatus
Categorical

 No AttritionAttrition
Distinct33
Distinct (%)0.2%1.3%
Missing00
Missing (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
Married
589 
Single
350 
Divorced
294 
Single
120 
Married
84 
Divorced
33 

Length

 No AttritionAttrition
Max length88
Median length76
Mean length6.95458236.6329114
Min length66

Characters and Unicode

 No AttritionAttrition
Total characters85751572
Distinct characters1414
Distinct categories22 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 No AttritionAttrition
Unique00 ?
Unique (%)0.0%0.0%

Sample

 No AttritionAttrition
1st rowMarriedSingle
2nd rowMarriedSingle
3rd rowMarriedSingle
4th rowSingleSingle
5th rowMarriedSingle

Common Values

ValueCountFrequency (%)
Married 589
47.8%
Single 350
28.4%
Divorced 294
23.8%
ValueCountFrequency (%)
Single 120
50.6%
Married 84
35.4%
Divorced 33
 
13.9%

Length

2023-05-20T15:44:02.686116image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

No Attrition

2023-05-20T15:44:02.811121image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:44:02.904848image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
married 589
47.8%
single 350
28.4%
divorced 294
23.8%
ValueCountFrequency (%)
single 120
50.6%
married 84
35.4%
divorced 33
 
13.9%

Most occurring characters

ValueCountFrequency (%)
r 1472
17.2%
i 1233
14.4%
e 1233
14.4%
d 883
10.3%
M 589
6.9%
a 589
6.9%
S 350
 
4.1%
n 350
 
4.1%
g 350
 
4.1%
l 350
 
4.1%
Other values (4) 1176
13.7%
ValueCountFrequency (%)
i 237
15.1%
e 237
15.1%
r 201
12.8%
S 120
7.6%
n 120
7.6%
g 120
7.6%
l 120
7.6%
d 117
7.4%
M 84
 
5.3%
a 84
 
5.3%
Other values (4) 132
8.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7342
85.6%
Uppercase Letter 1233
 
14.4%
ValueCountFrequency (%)
Lowercase Letter 1335
84.9%
Uppercase Letter 237
 
15.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 1472
20.0%
i 1233
16.8%
e 1233
16.8%
d 883
12.0%
a 589
8.0%
n 350
 
4.8%
g 350
 
4.8%
l 350
 
4.8%
v 294
 
4.0%
o 294
 
4.0%
ValueCountFrequency (%)
i 237
17.8%
e 237
17.8%
r 201
15.1%
n 120
9.0%
g 120
9.0%
l 120
9.0%
d 117
8.8%
a 84
 
6.3%
v 33
 
2.5%
o 33
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
M 589
47.8%
S 350
28.4%
D 294
23.8%
ValueCountFrequency (%)
S 120
50.6%
M 84
35.4%
D 33
 
13.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 8575
100.0%
ValueCountFrequency (%)
Latin 1572
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 1472
17.2%
i 1233
14.4%
e 1233
14.4%
d 883
10.3%
M 589
6.9%
a 589
6.9%
S 350
 
4.1%
n 350
 
4.1%
g 350
 
4.1%
l 350
 
4.1%
Other values (4) 1176
13.7%
ValueCountFrequency (%)
i 237
15.1%
e 237
15.1%
r 201
12.8%
S 120
7.6%
n 120
7.6%
g 120
7.6%
l 120
7.6%
d 117
7.4%
M 84
 
5.3%
a 84
 
5.3%
Other values (4) 132
8.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8575
100.0%
ValueCountFrequency (%)
ASCII 1572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 1472
17.2%
i 1233
14.4%
e 1233
14.4%
d 883
10.3%
M 589
6.9%
a 589
6.9%
S 350
 
4.1%
n 350
 
4.1%
g 350
 
4.1%
l 350
 
4.1%
Other values (4) 1176
13.7%
ValueCountFrequency (%)
i 237
15.1%
e 237
15.1%
r 201
12.8%
S 120
7.6%
n 120
7.6%
g 120
7.6%
l 120
7.6%
d 117
7.4%
M 84
 
5.3%
a 84
 
5.3%
Other values (4) 132
8.4%

MonthlyIncome
Real number (ℝ)

 No AttritionAttrition
Distinct1155233
Distinct (%)93.7%98.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean6832.73974787.0928
 No AttritionAttrition
Minimum10511009
Maximum1999919859
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
2023-05-20T15:44:03.041033image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

 No AttritionAttrition
Minimum10511009
5-th percentile2172.81594.6
Q132112373
median52043202
Q388345916
95-th percentile18105.411053
Maximum1999919859
Range1894818850
Interquartile range (IQR)56233543

Descriptive statistics

 No AttritionAttrition
Standard deviation4818.2083640.2104
Coefficient of variation (CV)0.705164870.76042193
Kurtosis0.67164054.1818449
Mean6832.73974787.0928
Median Absolute Deviation (MAD)23331128
Skewness1.28623141.9211469
Sum84247681134541
Variance2321512813251132
MonotonicityNot monotonicNot monotonic
2023-05-20T15:44:03.203001image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2559 3
 
0.2%
3452 3
 
0.2%
2451 3
 
0.2%
5562 3
 
0.2%
6142 3
 
0.2%
2342 3
 
0.2%
6347 3
 
0.2%
2096 2
 
0.2%
2109 2
 
0.2%
3294 2
 
0.2%
Other values (1145) 1206
97.8%
ValueCountFrequency (%)
5346 2
 
0.8%
2293 2
 
0.8%
2362 2
 
0.8%
2404 2
 
0.8%
5993 1
 
0.4%
13695 1
 
0.4%
18824 1
 
0.4%
2625 1
 
0.4%
7978 1
 
0.4%
3339 1
 
0.4%
Other values (223) 223
94.1%
ValueCountFrequency (%)
1051 1
0.1%
1052 1
0.1%
1129 1
0.1%
1200 1
0.1%
1223 1
0.1%
1232 1
0.1%
1274 1
0.1%
1281 1
0.1%
1483 1
0.1%
1514 1
0.1%
ValueCountFrequency (%)
1009 1
0.4%
1081 1
0.4%
1091 1
0.4%
1102 1
0.4%
1118 1
0.4%
1261 1
0.4%
1359 1
0.4%
1393 1
0.4%
1416 1
0.4%
1420 1
0.4%
ValueCountFrequency (%)
1009 1
0.1%
1081 1
0.1%
1091 1
0.1%
1102 1
0.1%
1118 1
0.1%
1261 1
0.1%
1359 1
0.1%
1393 1
0.1%
1416 1
0.1%
1420 1
0.1%
ValueCountFrequency (%)
1051 1
0.4%
1052 1
0.4%
1129 1
0.4%
1200 1
0.4%
1223 1
0.4%
1232 1
0.4%
1274 1
0.4%
1281 1
0.4%
1483 1
0.4%
1514 1
0.4%

MonthlyRate
Real number (ℝ)

 No AttritionAttrition
Distinct1208236
Distinct (%)98.0%99.6%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean14265.77914559.308
 No AttritionAttrition
Minimum20942326
Maximum2699726999
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
2023-05-20T15:44:03.374835image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

 No AttritionAttrition
Minimum20942326
5-th percentile3419.83338.2
Q179738870
median1412014618
Q32036421081
95-th percentile2535025771.2
Maximum2699726999
Range2490324673
Interquartile range (IQR)1239112211

Descriptive statistics

 No AttritionAttrition
Standard deviation7102.26077208.1533
Coefficient of variation (CV)0.497852980.495089
Kurtosis-1.2197282-1.1944349
Mean14265.77914559.308
Median Absolute Deviation (MAD)62156299
Skewness0.0199240060.0092522757
Sum175897063450556
Variance5044210851957473
MonotonicityNot monotonicNot monotonic
2023-05-20T15:44:03.641681image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2755 2
 
0.2%
15891 2
 
0.2%
8952 2
 
0.2%
6670 2
 
0.2%
25326 2
 
0.2%
9096 2
 
0.2%
11737 2
 
0.2%
11591 2
 
0.2%
6881 2
 
0.2%
24444 2
 
0.2%
Other values (1198) 1213
98.4%
ValueCountFrequency (%)
9150 2
 
0.8%
19479 1
 
0.4%
23288 1
 
0.4%
25308 1
 
0.4%
14075 1
 
0.4%
17285 1
 
0.4%
22845 1
 
0.4%
22154 1
 
0.4%
17235 1
 
0.4%
21534 1
 
0.4%
Other values (226) 226
95.4%
ValueCountFrequency (%)
2094 1
0.1%
2097 1
0.1%
2104 1
0.1%
2112 1
0.1%
2122 1
0.1%
2125 2
0.2%
2137 1
0.1%
2227 1
0.1%
2243 1
0.1%
2253 1
0.1%
ValueCountFrequency (%)
2326 1
0.4%
2396 1
0.4%
2447 1
0.4%
2493 1
0.4%
2993 1
0.4%
3020 1
0.4%
3064 1
0.4%
3072 1
0.4%
3129 1
0.4%
3157 1
0.4%
ValueCountFrequency (%)
2326 1
0.1%
2396 1
0.1%
2447 1
0.1%
2493 1
0.1%
2993 1
0.1%
3020 1
0.1%
3064 1
0.1%
3072 1
0.1%
3129 1
0.1%
3157 1
0.1%
ValueCountFrequency (%)
2094 1
0.4%
2097 1
0.4%
2104 1
0.4%
2112 1
0.4%
2122 1
0.4%
2125 2
0.8%
2137 1
0.4%
2227 1
0.4%
2243 1
0.4%
2253 1
0.4%

NumCompaniesWorked
Real number (ℝ)

 No AttritionAttrition
Distinct1010
Distinct (%)0.8%4.2%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean2.64557992.9409283
 No AttritionAttrition
Minimum00
Maximum99
Zeros17423
Zeros (%)14.1%9.7%
Negative00
Negative (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
2023-05-20T15:44:03.763643image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

 No AttritionAttrition
Minimum00
5-th percentile00
Q111
median21
Q345
95-th percentile88.2
Maximum99
Range99
Interquartile range (IQR)34

Descriptive statistics

 No AttritionAttrition
Standard deviation2.46009032.6785186
Coefficient of variation (CV)0.929886970.91077318
Kurtosis0.14143325-0.54306359
Mean2.64557992.9409283
Median Absolute Deviation (MAD)11
Skewness1.05879530.86416962
Sum3262697
Variance6.05204427.1744618
MonotonicityNot monotonicNot monotonic
2023-05-20T15:44:03.841749image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 423
34.3%
0 174
14.1%
3 143
 
11.6%
2 130
 
10.5%
4 122
 
9.9%
7 57
 
4.6%
6 54
 
4.4%
5 47
 
3.8%
8 43
 
3.5%
9 40
 
3.2%
ValueCountFrequency (%)
1 98
41.4%
0 23
 
9.7%
7 17
 
7.2%
4 17
 
7.2%
6 16
 
6.8%
5 16
 
6.8%
2 16
 
6.8%
3 16
 
6.8%
9 12
 
5.1%
8 6
 
2.5%
ValueCountFrequency (%)
0 174
14.1%
1 423
34.3%
2 130
 
10.5%
3 143
 
11.6%
4 122
 
9.9%
5 47
 
3.8%
6 54
 
4.4%
7 57
 
4.6%
8 43
 
3.5%
9 40
 
3.2%
ValueCountFrequency (%)
0 23
 
9.7%
1 98
41.4%
2 16
 
6.8%
3 16
 
6.8%
4 17
 
7.2%
5 16
 
6.8%
6 16
 
6.8%
7 17
 
7.2%
8 6
 
2.5%
9 12
 
5.1%
ValueCountFrequency (%)
0 23
 
1.9%
1 98
7.9%
2 16
 
1.3%
3 16
 
1.3%
4 17
 
1.4%
5 16
 
1.3%
6 16
 
1.3%
7 17
 
1.4%
8 6
 
0.5%
9 12
 
1.0%
ValueCountFrequency (%)
0 174
73.4%
1 423
178.5%
2 130
 
54.9%
3 143
 
60.3%
4 122
 
51.5%
5 47
 
19.8%
6 54
 
22.8%
7 57
 
24.1%
8 43
 
18.1%
9 40
 
16.9%

Over18
Boolean

 No AttritionAttrition
Distinct11
Distinct (%)0.1%0.4%
Missing00
Missing (%)0.0%0.0%
Memory size10.8 KiB3.7 KiB
True
1233 
Y
237 
ValueCountFrequency (%)
True 1233
100.0%
ValueCountFrequency (%)
Y 237
100.0%

No Attrition

2023-05-20T15:44:03.951098image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:44:04.010293image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

OverTime
Boolean

 No AttritionAttrition
Distinct22
Distinct (%)0.2%0.8%
Missing00
Missing (%)0.0%0.0%
Memory size10.8 KiB3.7 KiB
False
944 
True
289 
Yes
127 
No
110 
ValueCountFrequency (%)
False 944
76.6%
True 289
 
23.4%
ValueCountFrequency (%)
Yes 127
53.6%
No 110
46.4%

No Attrition

2023-05-20T15:44:04.088434image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:44:04.181233image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

PercentSalaryHike
Real number (ℝ)

 No AttritionAttrition
Distinct1515
Distinct (%)1.2%6.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean15.23114415.097046
 No AttritionAttrition
Minimum1111
Maximum2525
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
2023-05-20T15:44:04.249119image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

 No AttritionAttrition
Minimum1111
5-th percentile1111
Q11212
median1414
Q31817
95-th percentile2223
Maximum2525
Range1414
Interquartile range (IQR)65

Descriptive statistics

 No AttritionAttrition
Standard deviation3.63951133.7702942
Coefficient of variation (CV)0.238951940.24973721
Kurtosis-0.29233886-0.31615622
Mean15.23114415.097046
Median Absolute Deviation (MAD)22
Skewness0.815342280.8596967
Sum187803578
Variance13.24604214.215118
MonotonicityNot monotonicNot monotonic
2023-05-20T15:44:04.358434image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
14 177
14.4%
13 175
14.2%
11 169
13.7%
12 165
13.4%
15 83
6.7%
18 76
6.2%
17 68
 
5.5%
19 67
 
5.4%
16 64
 
5.2%
20 48
 
3.9%
Other values (5) 141
11.4%
ValueCountFrequency (%)
11 41
17.3%
13 34
14.3%
12 33
13.9%
14 24
10.1%
15 18
7.6%
16 14
 
5.9%
17 14
 
5.9%
18 13
 
5.5%
22 12
 
5.1%
19 9
 
3.8%
Other values (5) 25
10.5%
ValueCountFrequency (%)
11 169
13.7%
12 165
13.4%
13 175
14.2%
14 177
14.4%
15 83
6.7%
16 64
 
5.2%
17 68
 
5.5%
18 76
6.2%
19 67
 
5.4%
20 48
 
3.9%
ValueCountFrequency (%)
11 41
17.3%
12 33
13.9%
13 34
14.3%
14 24
10.1%
15 18
7.6%
16 14
 
5.9%
17 14
 
5.9%
18 13
 
5.5%
19 9
 
3.8%
20 7
 
3.0%
ValueCountFrequency (%)
11 41
3.3%
12 33
2.7%
13 34
2.8%
14 24
1.9%
15 18
1.5%
16 14
 
1.1%
17 14
 
1.1%
18 13
 
1.1%
19 9
 
0.7%
20 7
 
0.6%
ValueCountFrequency (%)
11 169
71.3%
12 165
69.6%
13 175
73.8%
14 177
74.7%
15 83
35.0%
16 64
 
27.0%
17 68
 
28.7%
18 76
32.1%
19 67
 
28.3%
20 48
 
20.3%

PerformanceRating
Categorical

 No AttritionAttrition
Distinct22
Distinct (%)0.2%0.8%
Missing00
Missing (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
3
1044 
4
189 
3
200 
4
37 

Length

 No AttritionAttrition
Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

 No AttritionAttrition
Total characters1233237
Distinct characters22
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 No AttritionAttrition
Unique00 ?
Unique (%)0.0%0.0%

Sample

 No AttritionAttrition
1st row43
2nd row33
3rd row33
4th row34
5th row43

Common Values

ValueCountFrequency (%)
3 1044
84.7%
4 189
 
15.3%
ValueCountFrequency (%)
3 200
84.4%
4 37
 
15.6%

Length

2023-05-20T15:44:04.452197image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

No Attrition

2023-05-20T15:44:04.557227image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:44:04.635334image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
3 1044
84.7%
4 189
 
15.3%
ValueCountFrequency (%)
3 200
84.4%
4 37
 
15.6%

Most occurring characters

ValueCountFrequency (%)
3 1044
84.7%
4 189
 
15.3%
ValueCountFrequency (%)
3 200
84.4%
4 37
 
15.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1233
100.0%
ValueCountFrequency (%)
Decimal Number 237
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 1044
84.7%
4 189
 
15.3%
ValueCountFrequency (%)
3 200
84.4%
4 37
 
15.6%

Most occurring scripts

ValueCountFrequency (%)
Common 1233
100.0%
ValueCountFrequency (%)
Common 237
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 1044
84.7%
4 189
 
15.3%
ValueCountFrequency (%)
3 200
84.4%
4 37
 
15.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1233
100.0%
ValueCountFrequency (%)
ASCII 237
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 1044
84.7%
4 189
 
15.3%
ValueCountFrequency (%)
3 200
84.4%
4 37
 
15.6%

RelationshipSatisfaction
Categorical

 No AttritionAttrition
Distinct44
Distinct (%)0.3%1.7%
Missing00
Missing (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
3
388 
4
368 
2
258 
1
219 
3
71 
4
64 
1
57 
2
45 

Length

 No AttritionAttrition
Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

 No AttritionAttrition
Total characters1233237
Distinct characters44
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 No AttritionAttrition
Unique00 ?
Unique (%)0.0%0.0%

Sample

 No AttritionAttrition
1st row41
2nd row32
3rd row42
4th row32
5th row13

Common Values

ValueCountFrequency (%)
3 388
31.5%
4 368
29.8%
2 258
20.9%
1 219
17.8%
ValueCountFrequency (%)
3 71
30.0%
4 64
27.0%
1 57
24.1%
2 45
19.0%

Length

2023-05-20T15:44:04.717476image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

No Attrition

2023-05-20T15:44:04.826825image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:44:04.920554image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
3 388
31.5%
4 368
29.8%
2 258
20.9%
1 219
17.8%
ValueCountFrequency (%)
3 71
30.0%
4 64
27.0%
1 57
24.1%
2 45
19.0%

Most occurring characters

ValueCountFrequency (%)
3 388
31.5%
4 368
29.8%
2 258
20.9%
1 219
17.8%
ValueCountFrequency (%)
3 71
30.0%
4 64
27.0%
1 57
24.1%
2 45
19.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1233
100.0%
ValueCountFrequency (%)
Decimal Number 237
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 388
31.5%
4 368
29.8%
2 258
20.9%
1 219
17.8%
ValueCountFrequency (%)
3 71
30.0%
4 64
27.0%
1 57
24.1%
2 45
19.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1233
100.0%
ValueCountFrequency (%)
Common 237
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 388
31.5%
4 368
29.8%
2 258
20.9%
1 219
17.8%
ValueCountFrequency (%)
3 71
30.0%
4 64
27.0%
1 57
24.1%
2 45
19.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1233
100.0%
ValueCountFrequency (%)
ASCII 237
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 388
31.5%
4 368
29.8%
2 258
20.9%
1 219
17.8%
ValueCountFrequency (%)
3 71
30.0%
4 64
27.0%
1 57
24.1%
2 45
19.0%

StandardHours
Categorical

 No AttritionAttrition
Distinct11
Distinct (%)0.1%0.4%
Missing00
Missing (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
80
1233 
80
237 

Length

 No AttritionAttrition
Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

 No AttritionAttrition
Total characters2466474
Distinct characters22
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 No AttritionAttrition
Unique00 ?
Unique (%)0.0%0.0%

Sample

 No AttritionAttrition
1st row8080
2nd row8080
3rd row8080
4th row8080
5th row8080

Common Values

ValueCountFrequency (%)
80 1233
100.0%
ValueCountFrequency (%)
80 237
100.0%

Length

2023-05-20T15:44:05.010983image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

No Attrition

2023-05-20T15:44:05.104745image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:44:05.188318image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
80 1233
100.0%
ValueCountFrequency (%)
80 237
100.0%

Most occurring characters

ValueCountFrequency (%)
8 1233
50.0%
0 1233
50.0%
ValueCountFrequency (%)
8 237
50.0%
0 237
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2466
100.0%
ValueCountFrequency (%)
Decimal Number 474
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 1233
50.0%
0 1233
50.0%
ValueCountFrequency (%)
8 237
50.0%
0 237
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2466
100.0%
ValueCountFrequency (%)
Common 474
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 1233
50.0%
0 1233
50.0%
ValueCountFrequency (%)
8 237
50.0%
0 237
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2466
100.0%
ValueCountFrequency (%)
ASCII 474
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 1233
50.0%
0 1233
50.0%
ValueCountFrequency (%)
8 237
50.0%
0 237
50.0%

StockOptionLevel
Categorical

 No AttritionAttrition
Distinct44
Distinct (%)0.3%1.7%
Missing00
Missing (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
1
540 
0
477 
2
146 
3
70 
0
154 
1
56 
3
 
15
2
 
12

Length

 No AttritionAttrition
Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

 No AttritionAttrition
Total characters1233237
Distinct characters44
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 No AttritionAttrition
Unique00 ?
Unique (%)0.0%0.0%

Sample

 No AttritionAttrition
1st row10
2nd row00
3rd row10
4th row00
5th row30

Common Values

ValueCountFrequency (%)
1 540
43.8%
0 477
38.7%
2 146
 
11.8%
3 70
 
5.7%
ValueCountFrequency (%)
0 154
65.0%
1 56
 
23.6%
3 15
 
6.3%
2 12
 
5.1%

Length

2023-05-20T15:44:05.258659image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

No Attrition

2023-05-20T15:44:05.353569image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:44:05.463443image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
1 540
43.8%
0 477
38.7%
2 146
 
11.8%
3 70
 
5.7%
ValueCountFrequency (%)
0 154
65.0%
1 56
 
23.6%
3 15
 
6.3%
2 12
 
5.1%

Most occurring characters

ValueCountFrequency (%)
1 540
43.8%
0 477
38.7%
2 146
 
11.8%
3 70
 
5.7%
ValueCountFrequency (%)
0 154
65.0%
1 56
 
23.6%
3 15
 
6.3%
2 12
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1233
100.0%
ValueCountFrequency (%)
Decimal Number 237
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 540
43.8%
0 477
38.7%
2 146
 
11.8%
3 70
 
5.7%
ValueCountFrequency (%)
0 154
65.0%
1 56
 
23.6%
3 15
 
6.3%
2 12
 
5.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1233
100.0%
ValueCountFrequency (%)
Common 237
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 540
43.8%
0 477
38.7%
2 146
 
11.8%
3 70
 
5.7%
ValueCountFrequency (%)
0 154
65.0%
1 56
 
23.6%
3 15
 
6.3%
2 12
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1233
100.0%
ValueCountFrequency (%)
ASCII 237
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 540
43.8%
0 477
38.7%
2 146
 
11.8%
3 70
 
5.7%
ValueCountFrequency (%)
0 154
65.0%
1 56
 
23.6%
3 15
 
6.3%
2 12
 
5.1%

TotalWorkingYears
Real number (ℝ)

 No AttritionAttrition
Distinct3932
Distinct (%)3.2%13.5%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean11.8629368.2447257
 No AttritionAttrition
Minimum00
Maximum3840
Zeros65
Zeros (%)0.5%2.1%
Negative00
Negative (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
2023-05-20T15:44:05.573929image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

 No AttritionAttrition
Minimum00
5-th percentile21
Q163
median107
Q31610
95-th percentile2823
Maximum3840
Range3840
Interquartile range (IQR)107

Descriptive statistics

 No AttritionAttrition
Standard deviation7.76071927.1692038
Coefficient of variation (CV)0.654198870.8695503
Kurtosis0.67807883.7840984
Mean11.8629368.2447257
Median Absolute Deviation (MAD)43
Skewness1.06692321.6881575
Sum146271954
Variance60.22876351.397483
MonotonicityNot monotonicNot monotonic
2023-05-20T15:44:05.718463image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
10 177
 
14.4%
6 103
 
8.4%
8 87
 
7.1%
9 86
 
7.0%
5 72
 
5.8%
7 63
 
5.1%
4 51
 
4.1%
12 43
 
3.5%
1 41
 
3.3%
15 35
 
2.8%
Other values (29) 475
38.5%
ValueCountFrequency (%)
1 40
16.9%
10 25
10.5%
6 22
 
9.3%
7 18
 
7.6%
8 16
 
6.8%
5 16
 
6.8%
4 12
 
5.1%
9 10
 
4.2%
3 9
 
3.8%
2 9
 
3.8%
Other values (22) 60
25.3%
ValueCountFrequency (%)
0 6
 
0.5%
1 41
 
3.3%
2 22
 
1.8%
3 33
 
2.7%
4 51
4.1%
5 72
5.8%
6 103
8.4%
7 63
5.1%
8 87
7.1%
9 86
7.0%
ValueCountFrequency (%)
0 5
 
2.1%
1 40
16.9%
2 9
 
3.8%
3 9
 
3.8%
4 12
 
5.1%
5 16
 
6.8%
6 22
9.3%
7 18
7.6%
8 16
 
6.8%
9 10
 
4.2%
ValueCountFrequency (%)
0 5
 
0.4%
1 40
3.2%
2 9
 
0.7%
3 9
 
0.7%
4 12
 
1.0%
5 16
 
1.3%
6 22
1.8%
7 18
1.5%
8 16
 
1.3%
9 10
 
0.8%
ValueCountFrequency (%)
0 6
 
2.5%
1 41
 
17.3%
2 22
 
9.3%
3 33
 
13.9%
4 51
21.5%
5 72
30.4%
6 103
43.5%
7 63
26.6%
8 87
36.7%
9 86
36.3%

TrainingTimesLastYear
Real number (ℝ)

 No AttritionAttrition
Distinct77
Distinct (%)0.6%3.0%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean2.83292782.6244726
 No AttritionAttrition
Minimum00
Maximum66
Zeros3915
Zeros (%)3.2%6.3%
Negative00
Negative (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
2023-05-20T15:44:05.839381image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

 No AttritionAttrition
Minimum00
5-th percentile10
Q122
median32
Q333
95-th percentile55
Maximum66
Range66
Interquartile range (IQR)11

Descriptive statistics

 No AttritionAttrition
Standard deviation1.29358531.2547842
Coefficient of variation (CV)0.456624870.47810908
Kurtosis0.447276040.65822486
Mean2.83292782.6244726
Median Absolute Deviation (MAD)11
Skewness0.590063860.33778676
Sum3493622
Variance1.67336291.5744833
MonotonicityNot monotonicNot monotonic
2023-05-20T15:44:05.917487image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2 449
36.4%
3 422
34.2%
5 105
 
8.5%
4 97
 
7.9%
1 62
 
5.0%
6 59
 
4.8%
0 39
 
3.2%
ValueCountFrequency (%)
2 98
41.4%
3 69
29.1%
4 26
 
11.0%
0 15
 
6.3%
5 14
 
5.9%
1 9
 
3.8%
6 6
 
2.5%
ValueCountFrequency (%)
0 39
 
3.2%
1 62
 
5.0%
2 449
36.4%
3 422
34.2%
4 97
 
7.9%
5 105
 
8.5%
6 59
 
4.8%
ValueCountFrequency (%)
0 15
 
6.3%
1 9
 
3.8%
2 98
41.4%
3 69
29.1%
4 26
 
11.0%
5 14
 
5.9%
6 6
 
2.5%
ValueCountFrequency (%)
0 15
 
1.2%
1 9
 
0.7%
2 98
7.9%
3 69
5.6%
4 26
 
2.1%
5 14
 
1.1%
6 6
 
0.5%
ValueCountFrequency (%)
0 39
 
16.5%
1 62
 
26.2%
2 449
189.5%
3 422
178.1%
4 97
 
40.9%
5 105
 
44.3%
6 59
 
24.9%

WorkLifeBalance
Categorical

 No AttritionAttrition
Distinct44
Distinct (%)0.3%1.7%
Missing00
Missing (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
3
766 
2
286 
4
126 
1
 
55
3
127 
2
58 
4
27 
1
25 

Length

 No AttritionAttrition
Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

 No AttritionAttrition
Total characters1233237
Distinct characters44
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 No AttritionAttrition
Unique00 ?
Unique (%)0.0%0.0%

Sample

 No AttritionAttrition
1st row31
2nd row33
3rd row33
4th row23
5th row23

Common Values

ValueCountFrequency (%)
3 766
62.1%
2 286
 
23.2%
4 126
 
10.2%
1 55
 
4.5%
ValueCountFrequency (%)
3 127
53.6%
2 58
24.5%
4 27
 
11.4%
1 25
 
10.5%

Length

2023-05-20T15:44:06.028135image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

No Attrition

2023-05-20T15:44:06.120926image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:44:06.233874image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
3 766
62.1%
2 286
 
23.2%
4 126
 
10.2%
1 55
 
4.5%
ValueCountFrequency (%)
3 127
53.6%
2 58
24.5%
4 27
 
11.4%
1 25
 
10.5%

Most occurring characters

ValueCountFrequency (%)
3 766
62.1%
2 286
 
23.2%
4 126
 
10.2%
1 55
 
4.5%
ValueCountFrequency (%)
3 127
53.6%
2 58
24.5%
4 27
 
11.4%
1 25
 
10.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1233
100.0%
ValueCountFrequency (%)
Decimal Number 237
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 766
62.1%
2 286
 
23.2%
4 126
 
10.2%
1 55
 
4.5%
ValueCountFrequency (%)
3 127
53.6%
2 58
24.5%
4 27
 
11.4%
1 25
 
10.5%

Most occurring scripts

ValueCountFrequency (%)
Common 1233
100.0%
ValueCountFrequency (%)
Common 237
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 766
62.1%
2 286
 
23.2%
4 126
 
10.2%
1 55
 
4.5%
ValueCountFrequency (%)
3 127
53.6%
2 58
24.5%
4 27
 
11.4%
1 25
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1233
100.0%
ValueCountFrequency (%)
ASCII 237
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 766
62.1%
2 286
 
23.2%
4 126
 
10.2%
1 55
 
4.5%
ValueCountFrequency (%)
3 127
53.6%
2 58
24.5%
4 27
 
11.4%
1 25
 
10.5%

YearsAtCompany
Real number (ℝ)

 No AttritionAttrition
Distinct3628
Distinct (%)2.9%11.8%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean7.36901875.1308017
 No AttritionAttrition
Minimum00
Maximum3740
Zeros2816
Zeros (%)2.3%6.8%
Negative00
Negative (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
2023-05-20T15:44:06.341832image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

 No AttritionAttrition
Minimum00
5-th percentile10
Q131
median63
Q3107
95-th percentile2016.2
Maximum3740
Range3740
Interquartile range (IQR)76

Descriptive statistics

 No AttritionAttrition
Standard deviation6.09629815.949984
Coefficient of variation (CV)0.827287651.1596597
Kurtosis3.35347319.6080291
Mean7.36901875.1308017
Median Absolute Deviation (MAD)32
Skewness1.65795822.6822444
Sum90861216
Variance37.16485135.40231
MonotonicityNot monotonicNot monotonic
2023-05-20T15:44:06.492147image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
5 175
14.2%
1 112
9.1%
3 108
8.8%
10 102
8.3%
2 100
 
8.1%
4 91
 
7.4%
7 79
 
6.4%
9 74
 
6.0%
8 71
 
5.8%
6 67
 
5.4%
Other values (26) 254
20.6%
ValueCountFrequency (%)
1 59
24.9%
2 27
11.4%
5 21
 
8.9%
3 20
 
8.4%
4 19
 
8.0%
10 18
 
7.6%
0 16
 
6.8%
7 11
 
4.6%
8 9
 
3.8%
6 9
 
3.8%
Other values (18) 28
11.8%
ValueCountFrequency (%)
0 28
 
2.3%
1 112
9.1%
2 100
8.1%
3 108
8.8%
4 91
7.4%
5 175
14.2%
6 67
 
5.4%
7 79
6.4%
8 71
5.8%
9 74
6.0%
ValueCountFrequency (%)
0 16
 
6.8%
1 59
24.9%
2 27
11.4%
3 20
 
8.4%
4 19
 
8.0%
5 21
 
8.9%
6 9
 
3.8%
7 11
 
4.6%
8 9
 
3.8%
9 8
 
3.4%
ValueCountFrequency (%)
0 16
 
1.3%
1 59
4.8%
2 27
2.2%
3 20
 
1.6%
4 19
 
1.5%
5 21
 
1.7%
6 9
 
0.7%
7 11
 
0.9%
8 9
 
0.7%
9 8
 
0.6%
ValueCountFrequency (%)
0 28
 
11.8%
1 112
47.3%
2 100
42.2%
3 108
45.6%
4 91
38.4%
5 175
73.8%
6 67
 
28.3%
7 79
33.3%
8 71
30.0%
9 74
31.2%

YearsInCurrentRole
Real number (ℝ)

 No AttritionAttrition
Distinct1915
Distinct (%)1.5%6.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean4.48418492.9029536
 No AttritionAttrition
Minimum00
Maximum1815
Zeros17173
Zeros (%)13.9%30.8%
Negative00
Negative (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
2023-05-20T15:44:06.606787image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

 No AttritionAttrition
Minimum00
5-th percentile00
Q120
median32
Q374
95-th percentile119
Maximum1815
Range1815
Interquartile range (IQR)54

Descriptive statistics

 No AttritionAttrition
Standard deviation3.64940193.1748268
Coefficient of variation (CV)0.813838411.093654
Kurtosis0.39056731.5672845
Mean4.48418492.9029536
Median Absolute Deviation (MAD)32
Skewness0.86072011.33536
Sum5529688
Variance13.31813410.079525
MonotonicityNot monotonicNot monotonic
2023-05-20T15:44:06.718837image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
2 304
24.7%
7 191
15.5%
0 171
13.9%
3 119
 
9.7%
4 89
 
7.2%
8 82
 
6.7%
9 61
 
4.9%
1 46
 
3.7%
6 35
 
2.8%
5 35
 
2.8%
Other values (9) 100
 
8.1%
ValueCountFrequency (%)
0 73
30.8%
2 68
28.7%
7 31
13.1%
3 16
 
6.8%
4 15
 
6.3%
1 11
 
4.6%
8 7
 
3.0%
9 6
 
2.5%
15 2
 
0.8%
10 2
 
0.8%
Other values (5) 6
 
2.5%
ValueCountFrequency (%)
0 171
13.9%
1 46
 
3.7%
2 304
24.7%
3 119
 
9.7%
4 89
 
7.2%
5 35
 
2.8%
6 35
 
2.8%
7 191
15.5%
8 82
 
6.7%
9 61
 
4.9%
ValueCountFrequency (%)
0 73
30.8%
1 11
 
4.6%
2 68
28.7%
3 16
 
6.8%
4 15
 
6.3%
5 1
 
0.4%
6 2
 
0.8%
7 31
13.1%
8 7
 
3.0%
9 6
 
2.5%
ValueCountFrequency (%)
0 73
5.9%
1 11
 
0.9%
2 68
5.5%
3 16
 
1.3%
4 15
 
1.2%
5 1
 
0.1%
6 2
 
0.2%
7 31
2.5%
8 7
 
0.6%
9 6
 
0.5%
ValueCountFrequency (%)
0 171
72.2%
1 46
 
19.4%
2 304
128.3%
3 119
 
50.2%
4 89
 
37.6%
5 35
 
14.8%
6 35
 
14.8%
7 191
80.6%
8 82
 
34.6%
9 61
 
25.7%

YearsSinceLastPromotion
Real number (ℝ)

 No AttritionAttrition
Distinct1614
Distinct (%)1.3%5.9%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean2.23438771.9451477
 No AttritionAttrition
Minimum00
Maximum1515
Zeros471110
Zeros (%)38.2%46.4%
Negative00
Negative (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
2023-05-20T15:44:06.827849image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

 No AttritionAttrition
Minimum00
5-th percentile00
Q100
median11
Q332
95-th percentile109
Maximum1515
Range1515
Interquartile range (IQR)32

Descriptive statistics

 No AttritionAttrition
Standard deviation3.23476223.1530769
Coefficient of variation (CV)1.44771751.6209961
Kurtosis3.43045184.8611443
Mean2.23438771.9451477
Median Absolute Deviation (MAD)11
Skewness1.94671022.2175628
Sum2755461
Variance10.4636879.9418937
MonotonicityNot monotonicNot monotonic
2023-05-20T15:44:06.937199image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 471
38.2%
1 308
25.0%
2 132
 
10.7%
7 60
 
4.9%
4 56
 
4.5%
3 43
 
3.5%
5 43
 
3.5%
6 26
 
2.1%
11 22
 
1.8%
8 18
 
1.5%
Other values (6) 54
 
4.4%
ValueCountFrequency (%)
0 110
46.4%
1 49
20.7%
2 27
 
11.4%
7 16
 
6.8%
3 9
 
3.8%
6 6
 
2.5%
4 5
 
2.1%
9 4
 
1.7%
15 3
 
1.3%
13 2
 
0.8%
Other values (4) 6
 
2.5%
ValueCountFrequency (%)
0 471
38.2%
1 308
25.0%
2 132
 
10.7%
3 43
 
3.5%
4 56
 
4.5%
5 43
 
3.5%
6 26
 
2.1%
7 60
 
4.9%
8 18
 
1.5%
9 13
 
1.1%
ValueCountFrequency (%)
0 110
46.4%
1 49
20.7%
2 27
 
11.4%
3 9
 
3.8%
4 5
 
2.1%
5 2
 
0.8%
6 6
 
2.5%
7 16
 
6.8%
9 4
 
1.7%
10 1
 
0.4%
ValueCountFrequency (%)
0 110
8.9%
1 49
4.0%
2 27
 
2.2%
3 9
 
0.7%
4 5
 
0.4%
5 2
 
0.2%
6 6
 
0.5%
7 16
 
1.3%
9 4
 
0.3%
10 1
 
0.1%
ValueCountFrequency (%)
0 471
198.7%
1 308
130.0%
2 132
 
55.7%
3 43
 
18.1%
4 56
 
23.6%
5 43
 
18.1%
6 26
 
11.0%
7 60
 
25.3%
8 18
 
7.6%
9 13
 
5.5%

YearsWithCurrManager
Real number (ℝ)

 No AttritionAttrition
Distinct1813
Distinct (%)1.5%5.5%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean4.36739662.8523207
 No AttritionAttrition
Minimum00
Maximum1714
Zeros17885
Zeros (%)14.4%35.9%
Negative00
Negative (%)0.0%0.0%
Memory size19.3 KiB3.7 KiB
2023-05-20T15:44:07.044214image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

 No AttritionAttrition
Minimum00
5-th percentile00
Q120
median32
Q375
95-th percentile118.2
Maximum1714
Range1714
Interquartile range (IQR)55

Descriptive statistics

 No AttritionAttrition
Standard deviation3.5941163.1433487
Coefficient of variation (CV)0.822942441.102032
Kurtosis0.139183530.2635281
Mean4.36739662.8523207
Median Absolute Deviation (MAD)32
Skewness0.801228511.0298503
Sum5385676
Variance12.917679.8806408
MonotonicityNot monotonicNot monotonic
2023-05-20T15:44:07.251318image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
2 294
23.8%
7 185
15.0%
0 178
14.4%
3 123
10.0%
8 97
 
7.9%
4 87
 
7.1%
1 65
 
5.3%
9 58
 
4.7%
5 27
 
2.2%
6 25
 
2.0%
Other values (8) 94
 
7.6%
ValueCountFrequency (%)
0 85
35.9%
2 50
21.1%
7 31
 
13.1%
3 19
 
8.0%
1 11
 
4.6%
4 11
 
4.6%
8 10
 
4.2%
9 6
 
2.5%
5 4
 
1.7%
6 4
 
1.7%
Other values (3) 6
 
2.5%
ValueCountFrequency (%)
0 178
14.4%
1 65
 
5.3%
2 294
23.8%
3 123
10.0%
4 87
 
7.1%
5 27
 
2.2%
6 25
 
2.0%
7 185
15.0%
8 97
 
7.9%
9 58
 
4.7%
ValueCountFrequency (%)
0 85
35.9%
1 11
 
4.6%
2 50
21.1%
3 19
 
8.0%
4 11
 
4.6%
5 4
 
1.7%
6 4
 
1.7%
7 31
 
13.1%
8 10
 
4.2%
9 6
 
2.5%
ValueCountFrequency (%)
0 85
6.9%
1 11
 
0.9%
2 50
4.1%
3 19
 
1.5%
4 11
 
0.9%
5 4
 
0.3%
6 4
 
0.3%
7 31
 
2.5%
8 10
 
0.8%
9 6
 
0.5%
ValueCountFrequency (%)
0 178
75.1%
1 65
 
27.4%
2 294
124.1%
3 123
51.9%
4 87
 
36.7%
5 27
 
11.4%
6 25
 
10.5%
7 185
78.1%
8 97
 
40.9%
9 58
 
24.5%

Interactions

No Attrition

2023-05-20T15:43:28.788662image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:54.864468image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:05.562615image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:33.529402image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:07.069503image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:35.111025image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:08.758878image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:36.587440image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:10.383519image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:38.054414image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:12.001648image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:39.559323image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:13.736553image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:41.136172image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:15.409103image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:42.692590image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:16.951975image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:44.213823image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:18.643635image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:45.622390image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:20.257823image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:47.103909image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:21.894550image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:48.746533image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:23.614812image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:50.225050image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:25.252098image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:51.763235image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:27.036442image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:53.355203image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:28.891031image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:54.973079image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:05.650476image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:33.633685image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:07.167603image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:35.212462image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:08.867157image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:36.688738image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:10.479218image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:38.151068image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:12.104201image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:39.663742image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:13.838029image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:41.243245image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:15.505219image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:42.790436image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:17.058816image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:44.310151image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:18.746403image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:45.725665image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:20.357593image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:47.210403image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:21.990909image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:48.847059image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:23.714223image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:50.331823image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:25.355028image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:51.867169image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:27.139386image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:53.450700image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:29.002115image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:55.072882image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:05.753029image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:33.730845image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:07.259985image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:35.305782image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:08.979720image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:36.787069image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:10.580584image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:38.245593image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:12.212832image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:39.763326image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:13.950117image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:41.345531image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:15.607307image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:42.874355image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:17.151623image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:44.404802image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:18.852294image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:45.822552image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:20.454597image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:47.311868image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:22.089409image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:48.943395image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:23.822079image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:50.430852image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:25.466683image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:51.966831image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:27.251075image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:53.563298image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:29.114550image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:55.174515image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:05.850858image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:33.827377image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:07.378414image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:35.401024image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:09.083878image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:36.879832image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:10.685363image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:38.338673image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:12.323162image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:39.863023image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:14.062146image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:41.446033image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:15.713081image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:42.979400image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:17.262892image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:44.497684image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:18.962038image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:45.921985image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:20.576317image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:47.414475image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:22.209265image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:49.038059image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:23.928466image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:50.532565image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:25.577820image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:52.065275image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:27.362530image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:53.662490image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:29.218549image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:55.265384image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:05.942737image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:33.918013image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:07.475570image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:35.487739image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:09.184046image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:36.969943image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:10.777541image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:38.422446image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:12.426883image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:39.953320image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:14.166448image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:41.540832image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:15.807546image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:43.064116image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:17.358917image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:44.582894image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:19.060281image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:46.011980image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:20.677051image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:47.508324image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:22.309226image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:49.128852image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:24.028429image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:50.625953image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:25.681852image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:52.156389image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:27.462524image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:53.753180image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:29.335970image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:55.369603image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:06.049258image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:34.019565image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:07.585916image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:35.590344image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:09.293394image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:37.068927image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:10.889176image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:38.518564image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:12.538889image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:40.056410image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:14.278735image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:41.645104image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:15.914505image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:43.160858image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:17.467604image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:44.678761image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:19.169455image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:46.113587image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:20.791314image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:47.613732image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:22.419871image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:49.228031image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:24.143345image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:50.731916image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:25.795851image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:52.258237image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:27.578260image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:53.855813image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:29.453042image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:55.473191image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:06.155227image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:34.125243image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:07.698776image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:35.698805image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:09.407846image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:37.172554image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:11.059673image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:38.617534image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:12.655976image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:40.159819image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:14.393264image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:41.749740image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:16.022367image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:43.260693image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:17.578578image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:44.778934image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:19.280870image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:46.217755image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:20.905961image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:47.718979image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:22.533552image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:49.331024image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:24.255655image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:50.837290image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:25.948639image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:52.362443image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:27.692898image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:53.960362image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:29.560375image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:55.566985image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:06.248981image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:34.215565image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:07.797465image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:35.789997image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:09.507218image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:37.260845image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:11.146748image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:38.701767image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:12.757121image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:40.238577image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:14.496414image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:41.842035image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:16.118869image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:43.343377image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:17.675859image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:44.862882image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:19.382313image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:46.293996image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:21.010639image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:47.815456image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:22.633094image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:49.436009image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:24.359832image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:50.930503image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:26.128369image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:52.457309image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:27.796739image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:54.052115image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:29.663964image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:55.658233image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:06.339419image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:34.304752image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:07.894131image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:35.868055image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:09.608104image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:37.353936image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:11.253486image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:38.789619image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:12.847880image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:40.341703image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:14.602990image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:41.936628image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:16.200755image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:43.428368image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:17.769232image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:44.948830image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:19.481933image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:46.396466image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:21.110972image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:47.895281image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:22.730887image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:49.525831image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:24.459733image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:51.024079image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:26.236302image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:52.547068image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:27.899239image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:54.146193image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:29.778652image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:55.760799image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:06.443031image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:34.402338image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:08.093136image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:35.976936image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:09.714415image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:37.449607image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:11.346927image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:38.882503image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:12.965805image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:40.439540image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:14.713336image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:42.038679image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:16.318361image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:43.522653image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:17.871984image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:45.041584image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:19.589875image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:46.490561image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:21.206355image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:48.011668image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:22.838889image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:49.622204image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:24.570030image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:51.128591image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:26.349132image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:52.645522image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:28.010093image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:54.242384image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:29.893135image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:55.867966image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:06.549779image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:34.597092image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:08.203121image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:36.082695image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:09.824278image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:37.551303image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:11.467379image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:38.982450image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:13.164926image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:40.548575image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:14.828166image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:42.149799image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:16.427070image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:43.624270image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:17.977663image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:45.145151image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:19.700900image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:46.598747image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:21.328118image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:48.118715image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:22.949957image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:49.726938image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:24.681417image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:51.236691image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:26.465069image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:52.752939image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:28.124871image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:54.349837image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:30.007208image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:56.024076image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:06.650359image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:34.700892image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:08.311495image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:36.181000image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:09.931532image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:37.636741image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:11.570746image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:39.169757image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:13.285119image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:40.648074image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:14.938253image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:42.262481image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:16.517720image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:43.708196image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:18.202733image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:45.224172image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:19.809538image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:46.696000image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:21.434952image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:48.218929image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:23.056468image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:49.821086image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:24.792878image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:51.337353image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:26.577167image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:52.850789image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:28.336530image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:54.447125image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:30.123037image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:56.137549image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:06.751933image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:34.802983image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:08.410784image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:36.285606image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:10.041721image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:37.751994image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:11.679509image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:39.254516image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:13.399445image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:40.752915image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:15.055580image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:42.372328image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:16.639887image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:43.818489image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:18.317221image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:45.335237image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:19.921000image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:46.801125image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:21.548516image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:48.326819image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:23.165554image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:49.926048image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:24.901938image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:51.443101image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:26.691564image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:52.959196image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:28.444752image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:54.555614image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:30.238079image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:56.242117image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:06.857946image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:34.904653image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:08.534416image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:36.385356image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:10.157547image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:37.852494image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:11.785501image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:39.366772image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:13.513125image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:40.860110image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:15.172644image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:42.480165image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:16.734726image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:44.020525image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:18.425761image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:45.430875image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:20.032877image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:46.901166image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:21.655720image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:48.432561image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:23.391782image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:50.023751image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:25.021154image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:51.551100image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:26.794048image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:53.058981image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:28.562950image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:54.661200image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:30.355349image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:56.343231image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:06.962758image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:35.007422image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:08.645314image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:36.485184image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:10.271634image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:37.953419image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:11.891365image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:39.463063image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:13.623990image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:41.028661image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:15.290033image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:42.585042image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:16.854432image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:44.116570image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:18.519447image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:45.526783image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:20.144977image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:47.002839image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:21.779442image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:48.537746image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:23.501909image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:50.114404image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:25.135312image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:51.656729image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:26.920235image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:53.254276image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

2023-05-20T15:43:28.673449image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:43:54.762283image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Correlations

No Attrition

2023-05-20T15:44:07.408329image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Attrition

2023-05-20T15:44:07.736184image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

No Attrition

AgeDailyRateDistanceFromHomeEmployeeNumberHourlyRateMonthlyIncomeMonthlyRateNumCompaniesWorkedPercentSalaryHikeTotalWorkingYearsTrainingTimesLastYearYearsAtCompanyYearsInCurrentRoleYearsSinceLastPromotionYearsWithCurrManagerBusinessTravelDepartmentEducationEducationFieldEnvironmentSatisfactionGenderJobInvolvementJobLevelJobRoleJobSatisfactionMaritalStatusOverTimePerformanceRatingRelationshipSatisfactionStockOptionLevelWorkLifeBalance
Age1.000-0.006-0.011-0.0110.0070.4460.0400.3680.0030.6420.0010.1870.1330.1460.1360.0480.0000.1480.0000.0220.0000.0070.2870.1650.0000.0940.0670.0000.0210.0600.024
DailyRate-0.0061.0000.014-0.0550.0110.001-0.0120.0270.0350.006-0.011-0.0170.001-0.045-0.0180.0070.0000.0000.0320.0000.0330.0270.0000.0000.0000.0890.0000.0000.0000.0540.032
DistanceFromHome-0.0110.0141.0000.0330.0330.0030.0400.0050.0090.009-0.0130.0330.0360.0030.0280.0520.0150.0000.0000.0000.0420.0590.0590.0000.0000.0000.0540.0660.0330.0400.000
EmployeeNumber-0.011-0.0550.0331.0000.029-0.0020.0170.0080.004-0.0100.0390.009-0.000-0.009-0.0050.0000.0000.0360.0000.0000.0070.0200.0240.0000.0000.0000.0000.0050.0580.0570.000
HourlyRate0.0070.0110.0330.0291.000-0.030-0.0150.023-0.000-0.019-0.011-0.038-0.040-0.049-0.0180.0000.0000.0270.0370.0000.0000.0000.0000.0170.0000.0390.0850.0000.0000.0640.022
MonthlyIncome0.4460.0010.003-0.002-0.0301.0000.0540.194-0.0270.701-0.0350.4260.3470.2350.3190.0380.1890.0910.0810.0000.0810.0400.8650.4200.0000.0410.0640.0430.0380.0470.000
MonthlyRate0.040-0.0120.0400.017-0.0150.0541.0000.023-0.0080.0340.001-0.0100.014-0.000-0.0130.0180.0000.0310.0000.0280.0000.0430.0160.0000.0490.0000.0000.0000.0420.0000.000
NumCompaniesWorked0.3680.0270.0050.0080.0230.1940.0231.0000.0090.318-0.056-0.199-0.150-0.085-0.1670.0000.0000.1080.0460.0000.0340.0000.1040.0750.0000.0220.0000.0450.0000.0000.037
PercentSalaryHike0.0030.0350.0090.004-0.000-0.027-0.0080.0091.000-0.025-0.013-0.048-0.015-0.048-0.0170.0440.0000.0470.0000.0000.0370.0440.0000.0150.0000.0000.0000.9970.0270.0000.000
TotalWorkingYears0.6420.0060.009-0.010-0.0190.7010.0340.318-0.0251.000-0.0150.5580.4520.3100.4520.0000.0000.1000.0000.0000.0790.0000.5040.2830.0680.0560.0520.0000.0000.0520.057
TrainingTimesLastYear0.001-0.011-0.0130.039-0.011-0.0350.001-0.056-0.013-0.0151.000-0.0020.0040.025-0.0090.0000.0000.0000.0350.0310.0000.0240.0000.0000.0450.0430.0850.0000.0000.0000.000
YearsAtCompany0.187-0.0170.0330.009-0.0380.426-0.010-0.199-0.0480.558-0.0021.0000.8420.4970.8290.0150.0510.0490.0160.0000.0950.0000.3240.1720.0000.0080.0800.0000.0000.0000.028
YearsInCurrentRole0.1330.0010.036-0.000-0.0400.3470.014-0.150-0.0150.4520.0040.8421.0000.4840.7030.0000.0000.0360.0000.0520.0890.0190.2220.1080.0000.0100.0800.0520.0000.0000.000
YearsSinceLastPromotion0.146-0.0450.003-0.009-0.0490.235-0.000-0.085-0.0480.3100.0250.4970.4841.0000.4370.0590.0000.0000.0000.0000.0000.0000.1960.1090.0000.0360.0000.0350.0460.0740.000
YearsWithCurrManager0.136-0.0180.028-0.005-0.0180.319-0.013-0.167-0.0170.452-0.0090.8290.7030.4371.0000.0800.0290.0000.0000.0000.0000.0070.2280.1100.0050.0000.0000.0500.0000.0000.055
BusinessTravel0.0480.0070.0520.0000.0000.0380.0180.0000.0440.0000.0000.0150.0000.0590.0801.0000.0000.0000.0000.0000.0340.0450.0000.0000.0290.0240.0000.0000.0000.0000.000
Department0.0000.0000.0150.0000.0000.1890.0000.0000.0000.0000.0000.0510.0000.0000.0290.0001.0000.0000.5720.0260.0430.0000.2140.9240.0450.0000.0000.0000.0270.0000.053
Education0.1480.0000.0000.0360.0270.0910.0310.1080.0470.1000.0000.0490.0360.0000.0000.0000.0001.0000.0500.0350.0000.0000.0800.0420.0310.0000.0390.0160.0000.0310.000
EducationField0.0000.0320.0000.0000.0370.0810.0000.0460.0000.0000.0350.0160.0000.0000.0000.0000.5720.0501.0000.0290.0000.0000.0970.3160.0410.0120.0000.0000.0610.0160.000
EnvironmentSatisfaction0.0220.0000.0000.0000.0000.0000.0280.0000.0000.0000.0310.0000.0520.0000.0000.0000.0260.0350.0291.0000.0000.0360.0000.0130.0000.0370.0950.0000.0000.0000.000
Gender0.0000.0330.0420.0070.0000.0810.0000.0340.0370.0790.0000.0950.0890.0000.0000.0340.0430.0000.0000.0001.0000.0320.0640.0710.0000.0290.0510.0000.0000.0000.000
JobInvolvement0.0070.0270.0590.0200.0000.0400.0430.0000.0440.0000.0240.0000.0190.0000.0070.0450.0000.0000.0000.0360.0321.0000.0000.0000.0000.0390.0000.0090.0000.0460.000
JobLevel0.2870.0000.0590.0240.0000.8650.0160.1040.0000.5040.0000.3240.2220.1960.2280.0000.2140.0800.0970.0000.0640.0001.0000.5650.0000.0000.0660.0000.0000.0480.000
JobRole0.1650.0000.0000.0000.0170.4200.0000.0750.0150.2830.0000.1720.1080.1090.1100.0000.9240.0420.3160.0130.0710.0000.5651.0000.0000.0000.0610.0000.0440.0000.061
JobSatisfaction0.0000.0000.0000.0000.0000.0000.0490.0000.0000.0680.0450.0000.0000.0000.0050.0290.0450.0310.0410.0000.0000.0000.0000.0001.0000.0190.0630.0000.0000.0000.000
MaritalStatus0.0940.0890.0000.0000.0390.0410.0000.0220.0000.0560.0430.0080.0100.0360.0000.0240.0000.0000.0120.0370.0290.0390.0000.0000.0191.0000.0610.0080.0550.5830.004
OverTime0.0670.0000.0540.0000.0850.0640.0000.0000.0000.0520.0850.0800.0800.0000.0000.0000.0000.0390.0000.0950.0510.0000.0660.0610.0630.0611.0000.0000.0390.0240.000
PerformanceRating0.0000.0000.0660.0050.0000.0430.0000.0450.9970.0000.0000.0000.0520.0350.0500.0000.0000.0160.0000.0000.0000.0090.0000.0000.0000.0080.0001.0000.0000.0280.000
RelationshipSatisfaction0.0210.0000.0330.0580.0000.0380.0420.0000.0270.0000.0000.0000.0000.0460.0000.0000.0270.0000.0610.0000.0000.0000.0000.0440.0000.0550.0390.0001.0000.0450.000
StockOptionLevel0.0600.0540.0400.0570.0640.0470.0000.0000.0000.0520.0000.0000.0000.0740.0000.0000.0000.0310.0160.0000.0000.0460.0480.0000.0000.5830.0240.0280.0451.0000.019
WorkLifeBalance0.0240.0320.0000.0000.0220.0000.0000.0370.0000.0570.0000.0280.0000.0000.0550.0000.0530.0000.0000.0000.0000.0000.0000.0610.0000.0040.0000.0000.0000.0191.000

Attrition

AgeDailyRateDistanceFromHomeEmployeeNumberHourlyRateMonthlyIncomeMonthlyRateNumCompaniesWorkedPercentSalaryHikeTotalWorkingYearsTrainingTimesLastYearYearsAtCompanyYearsInCurrentRoleYearsSinceLastPromotionYearsWithCurrManagerBusinessTravelDepartmentEducationEducationFieldEnvironmentSatisfactionGenderJobInvolvementJobLevelJobRoleJobSatisfactionMaritalStatusOverTimePerformanceRatingRelationshipSatisfactionStockOptionLevelWorkLifeBalance
Age1.0000.0360.0460.0390.1190.502-0.0840.3550.0200.686-0.0700.4270.3740.2720.3450.1050.0000.1890.0000.0000.0780.0000.3040.1600.0000.1940.0000.0000.0410.1610.041
DailyRate0.0361.000-0.073-0.0420.0790.049-0.1430.105-0.0290.040-0.028-0.026-0.014-0.0050.0110.0520.0000.0290.0260.0000.0000.1230.0630.0460.0000.0880.0000.0630.0600.0000.000
DistanceFromHome0.046-0.0731.0000.069-0.0300.0880.030-0.0990.1470.026-0.0550.005-0.011-0.022-0.0320.0000.0050.0000.1590.0000.0000.0000.0450.0740.0000.1070.0540.0000.0000.0520.000
EmployeeNumber0.039-0.0420.0691.0000.072-0.017-0.018-0.002-0.078-0.007-0.0480.009-0.0270.094-0.0360.0000.1400.0000.0820.0000.0900.0390.0000.0200.0500.0000.0540.0000.0000.0000.063
HourlyRate0.1190.079-0.0300.0721.0000.034-0.0210.002-0.0570.0310.0630.0130.015-0.0720.0110.0000.1310.0420.0770.0000.0940.0000.0000.0700.1220.0930.0000.0000.0000.0920.092
MonthlyIncome0.5020.0490.088-0.0170.0341.0000.0660.235-0.0750.683-0.0900.5060.4970.3810.4550.0000.2180.0000.0000.0360.1530.0980.8350.4500.0000.0000.0590.1080.0860.0740.079
MonthlyRate-0.084-0.1430.030-0.018-0.0210.0661.0000.0000.008-0.076-0.057-0.099-0.099-0.094-0.1260.0000.0000.0000.0000.0000.0000.0000.0000.0310.0590.0860.0000.0000.1100.0680.000
NumCompaniesWorked0.3550.105-0.099-0.0020.0020.2350.0001.000-0.0380.3940.0060.0110.0260.0340.0100.2080.0610.0950.0660.1090.0000.0510.1770.0780.0000.1170.0000.0000.0790.1210.062
PercentSalaryHike0.020-0.0290.147-0.078-0.057-0.0750.008-0.0381.000-0.0660.032-0.120-0.109-0.099-0.1070.1760.0000.0770.0000.1390.0000.0000.0000.0000.0540.0000.0000.9830.0750.0000.000
TotalWorkingYears0.6860.0400.026-0.0070.0310.683-0.0760.394-0.0661.000-0.0700.6850.6100.4470.6110.0000.0000.1830.0000.0000.0570.0580.5420.3270.0420.0750.0000.1160.0830.0000.103
TrainingTimesLastYear-0.070-0.028-0.055-0.0480.063-0.090-0.0570.0060.032-0.0701.000-0.044-0.039-0.082-0.0830.1380.0600.0000.0000.0770.0000.0000.0000.0000.0410.0000.0000.1220.1010.0000.000
YearsAtCompany0.427-0.0260.0050.0090.0130.506-0.0990.011-0.1200.685-0.0441.0000.9030.6360.8730.0000.0000.2280.0000.0000.0000.1740.5280.3070.0000.0240.0350.0000.0810.0000.000
YearsInCurrentRole0.374-0.014-0.011-0.0270.0150.497-0.0990.026-0.1090.610-0.0390.9031.0000.6190.7980.0000.0000.0000.0000.0300.0450.0910.4760.3510.0000.0790.0000.0000.0000.0000.000
YearsSinceLastPromotion0.272-0.005-0.0220.094-0.0720.381-0.0940.034-0.0990.447-0.0820.6360.6191.0000.5980.0000.0000.0310.0000.0000.0410.0000.3390.2390.0000.0860.1560.1010.0110.0610.000
YearsWithCurrManager0.3450.011-0.032-0.0360.0110.455-0.1260.010-0.1070.611-0.0830.8730.7980.5981.0000.0000.0000.0680.0000.0650.0000.0800.3490.2430.0420.1390.0000.0000.1240.0000.042
BusinessTravel0.1050.0520.0000.0000.0000.0000.0000.2080.1760.0000.1380.0000.0000.0000.0001.0000.0000.0000.0000.0000.0390.1330.0690.0000.0000.0490.0000.0690.0310.0000.000
Department0.0000.0000.0050.1400.1310.2180.0000.0610.0000.0000.0600.0000.0000.0000.0000.0001.0000.0000.6390.0000.0600.0080.2880.9810.0000.1430.0000.0830.0250.0400.030
Education0.1890.0290.0000.0000.0420.0000.0000.0950.0770.1830.0000.2280.0000.0310.0680.0000.0001.0000.0750.0490.0260.1540.0850.1150.0000.0000.0000.0000.1040.0000.027
EducationField0.0000.0260.1590.0820.0770.0000.0000.0660.0000.0000.0000.0000.0000.0000.0000.0000.6390.0751.0000.0530.0320.0000.0710.3880.0000.1530.0800.0000.0000.0500.086
EnvironmentSatisfaction0.0000.0000.0000.0000.0000.0360.0000.1090.1390.0000.0770.0000.0300.0000.0650.0000.0000.0490.0531.0000.0490.1090.0000.0000.0000.0000.1280.0000.0000.0560.031
Gender0.0780.0000.0000.0900.0940.1530.0000.0000.0000.0570.0000.0000.0450.0410.0000.0390.0600.0260.0320.0491.0000.0000.0000.0000.1170.0000.0000.0000.0940.0000.060
JobInvolvement0.0000.1230.0000.0390.0000.0980.0000.0510.0000.0580.0000.1740.0910.0000.0800.1330.0080.1540.0000.1090.0001.0000.1150.0000.0000.0000.0000.0000.0310.0120.000
JobLevel0.3040.0630.0450.0000.0000.8350.0000.1770.0000.5420.0000.5280.4760.3390.3490.0690.2880.0850.0710.0000.0000.1151.0000.6190.0000.0680.0000.0000.0520.0660.000
JobRole0.1600.0460.0740.0200.0700.4500.0310.0780.0000.3270.0000.3070.3510.2390.2430.0000.9810.1150.3880.0000.0000.0000.6191.0000.0000.1740.1350.0920.1340.1200.069
JobSatisfaction0.0000.0000.0000.0500.1220.0000.0590.0000.0540.0420.0410.0000.0000.0000.0420.0000.0000.0000.0000.0000.1170.0000.0000.0001.0000.0000.0000.1310.0000.0380.086
MaritalStatus0.1940.0880.1070.0000.0930.0000.0860.1170.0000.0750.0000.0240.0790.0860.1390.0490.1430.0000.1530.0000.0000.0000.0680.1740.0001.0000.0000.1280.0520.5380.000
OverTime0.0000.0000.0540.0540.0000.0590.0000.0000.0000.0000.0000.0350.0000.1560.0000.0000.0000.0000.0800.1280.0000.0000.0000.1350.0000.0001.0000.0000.1310.0000.050
PerformanceRating0.0000.0630.0000.0000.0000.1080.0000.0000.9830.1160.1220.0000.0000.1010.0000.0690.0830.0000.0000.0000.0000.0000.0000.0920.1310.1280.0001.0000.0000.0000.109
RelationshipSatisfaction0.0410.0600.0000.0000.0000.0860.1100.0790.0750.0830.1010.0810.0000.0110.1240.0310.0250.1040.0000.0000.0940.0310.0520.1340.0000.0520.1310.0001.0000.0000.055
StockOptionLevel0.1610.0000.0520.0000.0920.0740.0680.1210.0000.0000.0000.0000.0000.0610.0000.0000.0400.0000.0500.0560.0000.0120.0660.1200.0380.5380.0000.0000.0001.0000.001
WorkLifeBalance0.0410.0000.0000.0630.0920.0790.0000.0620.0000.1030.0000.0000.0000.0000.0420.0000.0300.0270.0860.0310.0600.0000.0000.0690.0860.0000.0500.1090.0550.0011.000

Missing values

No Attrition

2023-05-20T15:43:30.562375image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
A simple visualization of nullity by column.

Attrition

2023-05-20T15:43:56.551801image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
A simple visualization of nullity by column.

No Attrition

2023-05-20T15:43:31.055444image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Attrition

2023-05-20T15:43:57.033569image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

No Attrition

AgeAttritionBusinessTravelDailyRateDepartmentDistanceFromHomeEducationEducationFieldEmployeeCountEmployeeNumberEnvironmentSatisfactionGenderHourlyRateJobInvolvementJobLevelJobRoleJobSatisfactionMaritalStatusMonthlyIncomeMonthlyRateNumCompaniesWorkedOver18OverTimePercentSalaryHikePerformanceRatingRelationshipSatisfactionStandardHoursStockOptionLevelTotalWorkingYearsTrainingTimesLastYearWorkLifeBalanceYearsAtCompanyYearsInCurrentRoleYearsSinceLastPromotionYearsWithCurrManager
149NoTravel_Frequently279Research & Development81Life Sciences123Male6122Research Scientist2Married5130249071YNo2344801103310717
333NoTravel_Frequently1392Research & Development34Life Sciences154Female5631Research Scientist3Married2909231591YYes11338008338730
427NoTravel_Rarely591Research & Development21Medical171Male4031Laboratory Technician2Married3468166329YNo12348016332222
532NoTravel_Frequently1005Research & Development22Life Sciences184Male7931Laboratory Technician4Single3068118640YNo13338008227736
659NoTravel_Rarely1324Research & Development33Medical1103Female8141Laboratory Technician1Married267099644YYes204180312321000
730NoTravel_Rarely1358Research & Development241Life Sciences1114Male6731Laboratory Technician3Divorced2693133351YNo22428011231000
838NoTravel_Frequently216Research & Development233Life Sciences1124Male4423Manufacturing Director3Single952687870YNo214280010239718
936NoTravel_Rarely1299Research & Development273Medical1133Male9432Healthcare Representative3Married5237165776YNo133280217327777
1035NoTravel_Rarely809Research & Development163Medical1141Male8441Laboratory Technician2Married2426164790YNo13338016535403
1129NoTravel_Rarely153Research & Development152Life Sciences1154Female4922Laboratory Technician3Single4193126820YYes123480010339508

Attrition

AgeAttritionBusinessTravelDailyRateDepartmentDistanceFromHomeEducationEducationFieldEmployeeCountEmployeeNumberEnvironmentSatisfactionGenderHourlyRateJobInvolvementJobLevelJobRoleJobSatisfactionMaritalStatusMonthlyIncomeMonthlyRateNumCompaniesWorkedOver18OverTimePercentSalaryHikePerformanceRatingRelationshipSatisfactionStandardHoursStockOptionLevelTotalWorkingYearsTrainingTimesLastYearWorkLifeBalanceYearsAtCompanyYearsInCurrentRoleYearsSinceLastPromotionYearsWithCurrManager
041YesTravel_Rarely1102Sales12Life Sciences112Female9432Sales Executive4Single5993194798YYes11318008016405
237YesTravel_Rarely1373Research & Development22Other144Male9221Laboratory Technician3Single209023966YYes15328007330000
1428YesTravel_Rarely103Research & Development243Life Sciences1193Male5021Laboratory Technician3Single2028129475YYes14328006434203
2136YesTravel_Rarely1218Sales94Life Sciences1273Male8221Sales Representative1Single340769867YNo234280010435303
2434YesTravel_Rarely699Research & Development61Medical1312Male8331Research Scientist1Single2960171022YNo11338008234213
2632YesTravel_Frequently1125Research & Development161Life Sciences1332Female7211Research Scientist1Single391946811YYes2242800105310267
3339YesTravel_Rarely895Sales53Technical Degree1424Male5632Sales Representative4Married208633353YNo143380119641000
3424YesTravel_Rarely813Research & Development13Medical1452Male6131Research Scientist4Married229330202YYes16318016222020
3650YesTravel_Rarely869Sales32Marketing1471Male8621Sales Representative3Married268338101YYes14338003233202
4226YesTravel_Rarely1357Research & Development253Life Sciences1551Male4811Laboratory Technician3Single2293105581YNo12338001221001

No Attrition

AgeAttritionBusinessTravelDailyRateDepartmentDistanceFromHomeEducationEducationFieldEmployeeCountEmployeeNumberEnvironmentSatisfactionGenderHourlyRateJobInvolvementJobLevelJobRoleJobSatisfactionMaritalStatusMonthlyIncomeMonthlyRateNumCompaniesWorkedOver18OverTimePercentSalaryHikePerformanceRatingRelationshipSatisfactionStandardHoursStockOptionLevelTotalWorkingYearsTrainingTimesLastYearWorkLifeBalanceYearsAtCompanyYearsInCurrentRoleYearsSinceLastPromotionYearsWithCurrManager
145929NoTravel_Rarely1378Research & Development132Other120534Male4622Laboratory Technician2Married4025236794YYes133180110234303
146029NoTravel_Rarely468Research & Development284Medical120544Female7321Research Scientist1Single378584891YNo14328005315404
146239NoTravel_Rarely722Sales241Marketing120562Female6024Sales Executive4Married1203188280YNo1131801212220996
146331NoNon-Travel325Research & Development53Medical120572Male7432Manufacturing Director1Single993637870YNo193280010239417
146426NoTravel_Rarely1167Sales53Other120604Female3021Sales Representative3Single2966213780YNo18348005234200
146536NoTravel_Frequently884Research & Development232Medical120613Male4142Laboratory Technician4Married2571122904YNo173380117335203
146639NoTravel_Rarely613Research & Development61Medical120624Male4223Healthcare Representative1Married9991214574YNo15318019537717
146727NoTravel_Rarely155Research & Development43Life Sciences120642Male8742Manufacturing Director2Married614251741YYes20428016036203
146849NoTravel_Frequently1023Sales23Medical120654Male6322Sales Executive2Married5390132432YNo143480017329608
146934NoTravel_Rarely628Research & Development83Medical120682Male8242Laboratory Technician3Married4404102282YNo12318006344312

Attrition

AgeAttritionBusinessTravelDailyRateDepartmentDistanceFromHomeEducationEducationFieldEmployeeCountEmployeeNumberEnvironmentSatisfactionGenderHourlyRateJobInvolvementJobLevelJobRoleJobSatisfactionMaritalStatusMonthlyIncomeMonthlyRateNumCompaniesWorkedOver18OverTimePercentSalaryHikePerformanceRatingRelationshipSatisfactionStandardHoursStockOptionLevelTotalWorkingYearsTrainingTimesLastYearWorkLifeBalanceYearsAtCompanyYearsInCurrentRoleYearsSinceLastPromotionYearsWithCurrManager
137532YesTravel_Frequently238Research & Development52Life Sciences119391Female4741Research Scientist3Single2432153183YYes14318008234103
137927YesTravel_Frequently1337Human Resources223Human Resources119441Female5821Human Resources2Married2863195551YNo12318001231000
139028YesTravel_Rarely1404Research & Development173Technical Degree119603Male3221Laboratory Technician4Divorced2367187795YNo12318016224103
139531YesTravel_Frequently754Sales264Marketing119671Male6332Sales Executive4Married5617210751YYes1133800104310708
139653YesTravel_Rarely1168Sales244Life Sciences119681Male6633Sales Executive1Single1044858436YYes133280015222222
143823YesTravel_Frequently638Sales93Marketing120234Male3331Sales Representative1Married1790269561YNo19318011321010
144229YesTravel_Rarely1092Research & Development14Medical120271Male3631Research Scientist4Married4787261249YYes14328034342222
144456YesTravel_Rarely310Research & Development72Technical Degree120324Male7231Laboratory Technician3Married233936668YNo1134801144110998
145250YesTravel_Frequently878Sales14Life Sciences120442Male9432Sales Executive3Divorced6728142557YNo123480212336301
146150YesTravel_Rarely410Sales283Marketing120554Male3923Sales Executive1Divorced10854165864YYes133280120333220

Duplicate rows

No Attrition

AgeAttritionBusinessTravelDailyRateDepartmentDistanceFromHomeEducationEducationFieldEmployeeCountEmployeeNumberEnvironmentSatisfactionGenderHourlyRateJobInvolvementJobLevelJobRoleJobSatisfactionMaritalStatusMonthlyIncomeMonthlyRateNumCompaniesWorkedOver18OverTimePercentSalaryHikePerformanceRatingRelationshipSatisfactionStandardHoursStockOptionLevelTotalWorkingYearsTrainingTimesLastYearWorkLifeBalanceYearsAtCompanyYearsInCurrentRoleYearsSinceLastPromotionYearsWithCurrManager# duplicates
Dataset does not contain duplicate rows.

Attrition

AgeAttritionBusinessTravelDailyRateDepartmentDistanceFromHomeEducationEducationFieldEmployeeCountEmployeeNumberEnvironmentSatisfactionGenderHourlyRateJobInvolvementJobLevelJobRoleJobSatisfactionMaritalStatusMonthlyIncomeMonthlyRateNumCompaniesWorkedOver18OverTimePercentSalaryHikePerformanceRatingRelationshipSatisfactionStandardHoursStockOptionLevelTotalWorkingYearsTrainingTimesLastYearWorkLifeBalanceYearsAtCompanyYearsInCurrentRoleYearsSinceLastPromotionYearsWithCurrManager# duplicates
Dataset does not contain duplicate rows.